A bumpy ride on the diagnostic bench of massive parallel sequencing, the case of the mitochondrial genome

The advent of massive parallel sequencing (MPS) has revolutionized the field of human molecular genetics, including the diagnostic study of mitochondrial (mt) DNA dysfunction. The analysis of the complete mitochondrial genome using MPS platforms is now common and will soon outrun conventional sequencing. However, the development of a robust and reliable protocol is rather challenging. A previous pilot study for the re-sequencing of human mtDNA revealed an uneven coverage, affecting predominantly part of the plus strand. In an attempt to address this problem, we undertook a comparative study of standard and modified protocols for the Ion Torrent PGM system. We could not improve strand representation by altering the recommended shearing methodology of the standard workflow or omitting the DNA polymerase amplification step from the library construction process. However, we were able to associate coverage bias of the plus strand with a specific sequence motif. Additionally, we compared coverage and variant calling across technologies. The same samples were also sequenced on a MiSeq device which showed that coverage and heteroplasmic variant calling were much improved

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Accurate and comprehensive analysis of single nucleotide variants and large deletions of the human mitochondrial genome in DNA and single cells

Massive parallel sequencing (MPS) can accurately quantify mitochondrial DNA (mtDNA) single nucleotide variants (SNVs), but no MPS methods are currently validated to simultaneously and accurately establish the breakpoints and frequency of large deletions at low heteroplasmic loads. Here we present the thorough validation of an MPS protocol to quantify the load of very low frequency, large mtDNA deletions in bulk DNA and single cells, along with SNV calling by standard methods. We used a set of well-characterized DNA samples, DNA mixes and single cells to thoroughly control the study. We developed a custom script for the detection of mtDNA rearrangements that proved to be more accurate in detecting and quantifying deletions than pre-existing tools. We also show that PCR conditions and primersets must be carefully chosen to avoid biases in the retrieved variants and an increase in background noise, and established a lower detection limit of 0.5% heteroplasmic load for large deletions, and 1.5 and 2% for SNVs, for bulk DNA and single cells, respectively. Finally, the analysis of different single cells provided novel insights into mtDNA cellular mosaicism.European Journal of Human Genetics advance online publication, 23 August 2017; doi:10.1038/ejhg.2017.129.status: publishe

Liquid Biopsy-Derived DNA Sources as Tools for Comprehensive Mutation Profiling in Multiple Myeloma: A Comparative Study

The analysis of bone marrow (BM) samples in multiple myeloma (MM) patients can lead to the underestimation of the genetic heterogeneity within the tumor. Blood-derived liquid biopsies may provide a more comprehensive approach to genetic characterization. However, no thorough comparison between the currently available circulating biomarkers as tools for mutation profiling in MM has been published yet and the use of extracellular vesicle-derived DNA for this purpose in MM has not yet been investigated. Therefore, we collected BM aspirates and blood samples in 30 patients with active MM to isolate five different DNA types, i.e. cfDNA, EV-DNA, BM-DNA and DNA isolated from peripheral blood mononucleated cells (PBMNCs-DNA) and circulating tumor cells (CTC-DNA). DNA was analyzed for genetic variants with targeted gene sequencing using a 165-gene panel. After data filtering, 87 somatic and 39 germline variants were detected among the 149 DNA samples used for sequencing. cfDNA showed the highest concordance with the mutation profile observed in BM-DNA and outperformed EV-DNA, CTC-DNA and PBMNCs-DNA. Of note, 16% of all the somatic variants were only detectable in circulating biomarkers. Based on our analysis, cfDNA is the preferable circulating biomarker for genetic characterization in MM and its combined use with BM-DNA allows for comprehensive mutation profiling in MM.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Liquid Biopsy-Derived DNA Sources as Tools for Comprehensive Mutation Profiling in Multiple Myeloma: A Comparative Study

The analysis of bone marrow (BM) samples in multiple myeloma (MM) patients can lead to the underestimation of the genetic heterogeneity within the tumor. Blood-derived liquid biopsies may provide a more comprehensive approach to genetic characterization. However, no thorough comparison between the currently available circulating biomarkers as tools for mutation profiling in MM has been published yet and the use of extracellular vesicle-derived DNA for this purpose in MM has not yet been investigated. Therefore, we collected BM aspirates and blood samples in 30 patients with active MM to isolate five different DNA types, i.e., cfDNA, EV-DNA, BM-DNA and DNA isolated from peripheral blood mononucleated cells (PBMNCs-DNA) and circulating tumor cells (CTC-DNA). DNA was analyzed for genetic variants with targeted gene sequencing using a 165-gene panel. After data filtering, 87 somatic and 39 germline variants were detected among the 149 DNA samples used for sequencing. cfDNA showed the highest concordance with the mutation profile observed in BM-DNA and outperformed EV-DNA, CTC-DNA and PBMNCs-DNA. Of note, 16% of all the somatic variants were only detectable in circulating biomarkers. Based on our analysis, cfDNA is the preferable circulating biomarker for genetic characterization in MM and its combined use with BM-DNA allows for comprehensive mutation profiling in MM

Identification of candidate cancer predisposing variants by performing whole-exome sequencing on index patients from BRCA1 and BRCA2-negative breast cancer families

Abstract Background In the majority of familial breast cancer (BC) families, the etiology of the disease remains unresolved. To identify missing BC heritability resulting from relatively rare variants (minor allele frequency ≤ 1%), we have performed whole exome sequencing followed by variant analysis in a virtual panel of 492 cancer-associated genes on BC patients from BRCA1 and BRCA2 negative families with elevated BC risk. Methods BC patients from 54 BRCA1 and BRCA2-negative families with elevated BC risk and 120 matched controls were considered for germline DNA whole exome sequencing. Rare variants identified in the exome and in a virtual panel of cancer-associated genes [492 genes associated with different types of (hereditary) cancer] were compared between BC patients and controls. Nonsense, frame-shift indels and splice-site variants (strong protein-damaging variants, called PDAVs later on) observed in BC patients within the genes of the panel, which we estimated to possess the highest probability to predispose to BC, were further validated using an alternative sequencing procedure. Results Exome- and cancer-associated gene panel-wide variant analysis show that there is no significant difference in the average number of rare variants found in BC patients compared to controls. However, the genes in the cancer-associated gene panel with nonsense variants were more than two-fold over-represented in women with BC and commonly involved in the DNA double-strand break repair process. Approximately 44% (24 of 54) of BC patients harbored 31 PDAVs, of which 11 were novel. These variants were found in genes associated with known or suspected BC predisposition (PALB2, BARD1, CHEK2, RAD51C and FANCA) or in predisposing genes linked to other cancer types but not well-studied in the context of familial BC (EXO1, RECQL4, CCNH, MUS81, TDP1, DCLRE1A, DCLRE1C, PDE11A and RINT1) and genes associated with different hereditary syndromes but not yet clearly associated with familial cancer syndromes (ABCC11, BBS10, CD96, CYP1A1, DHCR7, DNAH11, ESCO2, FLT4, HPS6, MYH8, NME8 and TTC8). Exome-wide, only a few genes appeared to be enriched for PDAVs in the familial BC patients compared to controls. Conclusions We have identified a series of novel candidate BC predisposition variants/genes. These variants/genes should be further investigated in larger cohorts/case-control studies. Other studies including co-segregation analyses in affected families, locus-specific loss of heterozygosity and functional studies should shed further light on their relevance for BC risk

RNAseq data from quiescent amastigotes recovered from mouse LT-HSC.

(a) Principal component analysis (PCA) of the RNAseq data revealing distant clustering of the independent DsRedhi and quiescent samples. (b) Euclidean distance matrix between the samples illustrating the Poisson Distance. (c) Sorted amastigotes (DsRedhi and quiescent) of infected LT-HSC were RNA extracted and subjected to RT-dPCR for 18 target genes (S2 Table). (d) GO term analysis of 167 genes that are found to be expressed in the three independent quiescent Leishmania amastigote samples. Visual representation of GO terms enriched in biological processes, molecular function and cellular components. (TIF)</p

Phenotypic characteristics of promastigotes from relapsed BM.

(a) BALB/c mice were infected with 108 stationary phase promastigotes of L. infantum LEM3323 WTPpyRE9/DsRed. One group was treated with PMM 350 mg/kg per day (IP) for 5 consecutive days. Infection was followed up by BLI, BM was collected at 6 weeks post infection (wpi) from untreated and relapsed mice. (b) Stationary phase promastigotes recovered from relapsed BM (relapse) and untreated BM (infection) were co-incubated at a MOI of 5 with peritoneal macrophages for 96 hours and infectivity was assessed with Giemsa. Parasite cultures were counted and visually confirmed to contain > 90% metacyclics to exclude an infectivity bias based on the parasite culture (S6 Fig). Mann-Whitney test, n = 100, ***p S1 Table. (c) L. infantum LEM3323 promastigotes recovered from relapsed BM (relapse) and untreated BM (infection) were co-incubated with peritoneal macrophages for 24 hours and treated with 120 μM, 250 μM or 350 μM PMM for 72 hours, infectivity was assessed with Giemsa. (d) Sand flies were infected by L. infantum LEM3323 promastigotes recovered from relapsed BM (relapse) and untreated BM (infection) and the parasite load in the gut of infected flies was assessed at days 5, 7, 9 and 12 after infection (blood meal). Sand fly infections were repeated three independent times. 10 n < 32.</p

<i>Leishmania</i> infection of mouse LT-HSC and human HSPC triggers amastigote quiescence.

(a) Amastigotes recovered from infected mouse LT-HSC and measured via flow cytometry. Cells in the left panel were infected with L. infantum LEM3323 WTPpyRE9/DsRed, middle panel with L. infantum clinical isolate LLM2346 WTPpyRE9/DsRed, right panel with L. donovani Ldl82 WTPpyRE9/DsRed. (b) Amastigotes recovered from L. infantum LLM2346 WTPpyRE9/DsRed infected human HSPC. (c) BM derived macrophages were infected with L. infantum (LEM3323 WTPpyRE9/DsRed) and intracellular amastigotes were isolated and measured by flow cytometry. (d) DsRed expression measured by flow cytometry after promastigote back-transformation of DsRedhi and DsRedlo (i.e. quiescent) amastigotes recovered from LT-HSC. (e) L. infantum LEM3323 WTPpyRE9/DsRed amastigotes recovered from infected mouse LT-HSC and measured via flow cytometry, back-gated on SSC versus FSC. Mann-Whitney test, *p (f) Sorted mouse LT-HSC were infected with L. infantum (LEM3323 WTPpyRE9/DsRed) and processed for microscopy. DAPI (blue), amastigotes (red). Scale bar = 10 μm. (g) Analysis of microscopy images of (f) in the FIJI software, comparing the expression level of DsRed to its respective size.</p

Number of divisions associated with quiescence in amastigotes from mouse LT-HSC and human HSPC.

(a) Number of divisions as calculated by CFSE staining and defined by curve-fitting of the cellular CFSE-intensity using the Proliferation Analysis tool of FlowLogic (left panel). Controls are unstained and CFSE L. infantum (LEM3323 WTPpyRE9/DsRed) promastigote cultures. Sorted mouse LT-HSC were infected with CFSE labelled L. infantum promastigotes and amastigotes were recovered after 6 hours of co-incubation (right panel). (b) Percentage of cells in each division range from (a). Results are based on three independent repeats. (c) Number of divisions as calculated by CFSE staining using the Proliferation Analysis tool (left panel). Controls include unstained and CFSE-stained L. infantum (LLM2346 WTPpyRE9/DsRed) promastigote cultures. Sorted human HSPC were infected with CFSE labelled L. infantum promastigotes and amastigotes were recovered after 24 hours of co-incubation (right panel). (d) Percentage of cells in each division range from (c). Results are based on three independent repeats. (e) Early infection of L. infantum (LEM3323 WTPpyRE9/DsRed) in mouse LT-HSC at 1, 3, 6, and 24 hours post infection visualised by Giemsa staining. Amastigotes (arrow), promastigotes (dotted arrow), promastigotes transitioning to amastigotes, already without flagellum (asterisk), dividing amastigotes (red asterisk).</p