Analysis Of Whole Genome Sequencing Data Research Articles

Core Genome Multi-locus Sequence Typing Analyses of Leptospira spp. Using the Bacterial Isolate Genome Sequence Database.

With the advent of whole-genome sequencing (WGS), comparative analysis has led to the use of core genome MLST (cgMLST) schemes for the high-resolution reproducible typing of bacterial isolates. In cgMLST, hundreds of loci are used for gene-by-gene comparisons of assembled genomes for studying the genetic diversity of clinically important pathogens. Combination of the cgMLST data and metadata of the isolates is useful for epidemiological investigations.Here we present a cgMLST scheme for the high-resolution typing of isolates from the whole Leptospira genus, enabling identification at the level of species, clades, clonal groups, and sequence types. We show several examples how the cgMLST Leptospira database, which is a publicly available web-based database, can be used for the analyses of WGS data of Leptospira isolates. This effort was undertaken in order to facilitate international collaborations and support the global surveillance of leptospirosis.

BacPipe: A Rapid, User-Friendly Whole-Genome Sequencing Pipeline for Clinical Diagnostic Bacteriology.

SummaryDespite rapid advances in whole genome sequencing (WGS) technologies, their integration into routine microbiological diagnostics has been hampered by the lack of standardized downstream bioinformatics analysis. We developed a comprehensive and computationally low-resource bioinformatics pipeline (BacPipe) enabling direct analyses of bacterial whole-genome sequences (raw reads or contigs) obtained from second- or third-generation sequencing technologies. A graphical user interface was developed to visualize real-time progression of the analysis. The scalability and speed of BacPipe in handling large datasets was demonstrated using 4,139 Illumina paired-end sequence files of publicly available bacterial genomes (2.9–5.4 Mb) from the European Nucleotide Archive. BacPipe is integrated in EBI-SELECTA, a project-specific portal (H2020-COMPARE), and is available as an independent docker image that can be used across Windows- and Unix-based systems. BacPipe offers a fully automated “one-stop” bacterial WGS analysis pipeline to overcome the major hurdle of WGS data analysis in hospitals and public-health and for infection control monitoring.

Germline mutations in the transcription factor IKZF5 cause thrombocytopenia

AbstractTo identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing data from 13 037 individuals enrolled in the National Institute for Health Research (NIHR) BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor-encoding gene IKZF5 and thrombocytopenia. We report 5 causal missense variants in or near IKZF5 zinc fingers, of which 2 occurred de novo and 3 co-segregated in 3 pedigrees. A canonical DNA-zinc finger binding model predicts that 3 of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared with wild-type IKZF5, and electron microscopy revealed a reduced quantity of α granules in normally sized platelets. Proplatelet formation was reduced in megakaryocytes from 7 cases relative to 6 controls. Comparison of RNA-sequencing data from platelets, monocytes, neutrophils, and CD4+ T cells from 3 cases and 14 healthy controls showed 1194 differentially expressed genes in platelets but only 4 differentially expressed genes in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

Genotyping of Mycobacterium tuberculosis spreading in Hanoi, Vietnam using conventional and whole genome sequencing methods

Hanoi is the capital of Vietnam, one of the 30 countries with a high tuberculosis (TB) burden. Fundamental data on the molecular epidemiology of the disease is required for future TB management.To identify lineages and genotypes of Mycobacterium tuberculosis (Mtb), conventional genotyping data from clinical isolates of the Hanoi area was compared with whole genome sequencing (WGS) analysis from 332 of 470 samples. It was obtained from lineage-specific single nucleotide variants (SNVs), large sequence polymorphisms, spoligotyping, and variable number of tandem repeats (VNTR) analysis using mycobacterial interspersed repetitive unit (MIRU) and Japan anti-tuberculosis association (JATA) locus sets. This information was directly compared with results obtained from WGS. Mini-satellite repeat unit variants were identified using BLAST search against concatenated short read sequences, the RepUnitTyping tool.WGS analysis revealed that the Mtb strains tested are diverse and classified into lineage (L) 1, 2 and 4 (24.7, 57.2 and 18.1% respectively). The majority of the L2 strains were further divided into ancient and modern Beijing genotypes, and most of the L1 group were EAI4_VNM strains. Although conventional PCR-based genotyping results were mostly consistent with information obtained through WGS analysis, in-depth analysis identified aberrant deletions and spacers that may cause discordance. JATA-VNTR sets, including hypervariable loci, separated large Beijing genotypic clusters generated by MIRU15 into smaller groups. The distribution of repeat unit variants observed within 33 VNTR loci showed clear variation depending on the three lineages. WGS-based pairwise-SNV differences within VNTR-defined genotypic clusters were greater in L1 than in L2 and L4 (P = .001).Direct comparisons between results of PCR-based genotyping and in silico analysis of WGS data would bridge a gap between classical and modern technologies during this transition period, and provide further information on Mtb genotypes in specific geographical areas.

603. Identification of a Carbapenemase-Producing, Extensively Drug-Resistant Klebsiella pneumoniae Isolate Carrying a blaNDM-1-Bearing, Hypervirulent Plasmid, United States 2017

BackgroundThe recent discovery of carbapenemase-producing hypervirulent Klebsiella pneumoniae (CP-HvKP) has signaled the convergence of multidrug resistance and pathogenicity, with the potential for increased mortality. While previous studies of CP-HvKP isolates revealed that most carried carbapenemase genes and hypervirulence elements on separate plasmids, a 2018 report from China confirmed that both could be harbored on a single, hybrid carbapenemase-hypervirulent plasmid. As part of a project sequencing isolates carrying multiple carbapenemase genes identified through CDC’s Antibiotic Resistance Laboratory Network (AR Lab Network), we discovered a blaNDM-1-bearing hypervirulent plasmid found in a KPC- and NDM-positive K. pneumoniae from the United States.MethodsAntimicrobial susceptibility testing (AST) was performed by reference broth microdilution against 23 agents. Whole-genome sequencing (WGS) was performed on Illumina MiSeq and PacBio RS II platforms.ResultsAST results indicated the isolate was extensively drug-resistant, as it was non-susceptible to at least one agent in all but two drug classes; it was susceptible to only tigecycline and tetracycline. Analysis of WGS data showed the isolate was ST11, the same sequence type that caused a fatal outbreak of CP-HvKP in China in 2016. The genome included two plasmids. The smaller one (129kbp) carried seven antibiotic resistance (AR) genes, including the carbapenemase gene blaKPC-2. The larger plasmid (354kbp) harbored 11 AR genes, including the metallo-β-lactamase gene blaNDM-1, as well as virulence factors iucABCD/iutA, peg-344, rmpA, and rmpA2, which comprise four of the five genes previously identified as predictors of hypervirulence in K. pneumoniae.ConclusionThis is the first report of a hybrid carbapenemase-hypervirulent plasmid in the United States. The presence of both blaNDM-1 and hypervirulence elements on the same plasmid suggests that the CP-Hv pathotype could spread rapidly through horizontal transfer. This discovery demonstrates the critical role of genomic characterization of emerging resistance and virulence phenotypes by the AR Lab Network as part of US containment efforts.Disclosures All authors: No reported disclosures.

Molecular Characterization of Equine Staphylococcus aureus Isolates Exhibiting Reduced Oxacillin Susceptibility.

The detection of borderline oxacillin-resistant Staphylococcus aureus (BORSA) represents a challenge to both, veterinary and human laboratories. Between 2015 and 2017, 19 equine S. aureus with elevated minimal inhibitory concentrations for oxacillin were detected in routine diagnostics. The aim of this study was to characterize these isolates to identify factors possibly associated with the BORSA phenotype. All S. aureus were subjected to antimicrobial susceptibility testing and whole genome sequencing (WGS). A quantifiable β-lactamase activity assay was performed for a representative subset of 13 isolates. The WGS data analysis of the 19 BORSA isolates identified two different genomic lineages, sequence type (ST) 1 and ST1660. The core genome multilocus sequence typing (cgMLST) revealed a close relatedness of all isolates belonging to either ST1 or ST1660. The WGS analysis identified the resistance genes aadD, dfrG, tet(L), and/or blaZ and aacA-aphD. Phenotypic resistance to penicillins, aminoglycosides, tetracyclines, fluoroquinolones and sulfamethoxazole/trimethoprim was observed in the respective isolates. For the penicillin-binding proteins 1–4, amino acid substitutions were predicted using WGS data. Since neither transglycosylase nor transpeptidase domains were affected, these alterations might not explain the BORSA phenotype. Moreover, β-lactamase activity was found to be associated with an inducible blaZ gene. Lineage-specific differences regarding the expression profiles were noted.

Machine Learning Approaches for Epidemiological Investigations of Food-Borne Disease Outbreaks.

Foodborne diseases (FBDs) are infections of the gastrointestinal tract caused by foodborne pathogens (FBPs) such as bacteria [Salmonella, Listeria monocytogenes and Shiga toxin-producing E. coli (STEC)] and several viruses, but also parasites and some fungi. Artificial intelligence (AI) and its sub-discipline machine learning (ML) are re-emerging and gaining an ever increasing popularity in the scientific community and industry, and could lead to actionable knowledge in diverse ranges of sectors including epidemiological investigations of FBD outbreaks and antimicrobial resistance (AMR). As genotyping using whole-genome sequencing (WGS) is becoming more accessible and affordable, it is increasingly used as a routine tool for the detection of pathogens, and has the potential to differentiate between outbreak strains that are closely related, identify virulence/resistance genes and provide improved understanding of transmission events within hours to days. In most cases, the computational pipeline of WGS data analysis can be divided into four (though, not necessarily consecutive) major steps: de novo genome assembly, genome characterization, comparative genomics, and inference of phylogeny or phylogenomics. In each step, ML could be used to increase the speed and potentially the accuracy (provided increasing amounts of high-quality input data) of identification of the source of ongoing outbreaks, leading to more efficient treatment and prevention of additional cases. In this review, we explore whether ML or any other form of AI algorithms have already been proposed for the respective tasks and compare those with mechanistic model-based approaches.

28. KARYOMAPPING USING WHOLE GENOME SEQUENCING DATA: PRECLINICAL VALIDATION OF A PERSONALISED APPROACH TO PGT-M

Introduction Karyomapping utilises microarray technology to track informative single nucleotide polymorphisms (SNPs) and assign haplotypes to embryos without the need for direct mutation detection (Handyside et al. 2010). Although suitable for most couples undergoing PGT-M, the use of a fixed set of SNPs may provide inadequate information in certain genetic regions or in consanguineous couples (Konstantinidis et al. 2015). Whole genome sequencing (WGS) has the potential to individualise informative SNP detection and perform concurrent direct mutation detection. However, no studies have evaluated the potential for application of the karyomapping algorithm to WGS data. Material and Methods The Platinum Genomes dataset ( https://sapac.illumina.com/platinumgenomes.html ) was analysed as a model for the application of karyomapping to WGS data. Variant call format (VCF) files were analysed according to the principles of karyomapping to create a map of informative biallelic SNPs in each grandparental haplotype. A model of embryo biopsy was created by diluting DNA from one of the family members (NA12878) to 30pg and whole genome amplification was performed with the Repli-G single cell kit (Qiagen, Hilden, Germany) as a model of trophectoderm biopsy. Whole genome sequencing was performed in triplicate on a high output NextSeq 2500 run (Illumina, California, USA) at average 15x coverage and the number of informative SNPs detected compared to the karyomapping SNP microarray. Comparison of variant calling methods was performed using the Genome Analysis Toolkit v3.4 (Broad Institute, Massachusetts, USA) and DeepVariant (Google, California, USA). Results Analysis of WGS data from the Platinum Genomes family revealed a total of 2,338,158 informative SNPs distributed evenly between grandparental haplotypes, of which 85,053 (3.6%) would have been detectable using the karyomapping SNP array. Analysis of the karyomapping window around common genes requiring PGT-M demonstrated an average 32x increase in the number of targets available for analysis in a PGT-M cycle. Analysis of 15x coverage WGS data in a model of embryo biopsy demonstrated an average 279,851 informative SNPs detected using standard variant calling and an average 285,107 using AI-based variant calling. The median distance between informative SNPs was reduced from 26,782 nucleotides to 1,212 nucleotides when comparing WGS-based karyomapping to SNP array-based karyomapping. Conclusions This study provides preclinical validation for the application of the karyomapping algorithm to WGS data. The markedly increased number of informative SNPs will allow successful feasibility studies for all couples presenting for PGT-M. The decreased distance between informative SNPs detected in a model embryo biopsy will improve diagnostic accuracy, particularly in detecting small double crossover events and reducing the number of cycles in which inadequate informative markers have been detected in the embryo sample. Finally, the use of WGS for diagnostic purposes, especially for rare and undiagnosed genetic disease, will allow the creation of a high resolution digital karyomap for couples with an affected child and improve the transition to IVF and PGT-M.

A67 Bloodstream infections by carbapenem-resistant Klebsiella pneumoniae subsp. pneumoniae: Bayesian phylogenetic analysis of whole genomes

Bloodstream infection (BSI) caused by carbapenemase-producing Enterobacteriaceae (CPE) is a major public health concern, particularly in the hospital setting. The rapid detection of resistance patterns is of paramount importance for establishing the proper antibiotic regime. In addition, in countries where CPE are endemic, it is also important to evaluate genetic relationship among the isolates in order to trace pathogen circulation and to improve the infection control programs. This study is an application of a rapid blood culture (BC) workflow consisting of fast reporting of Gram stain results, rapid pathogen identification (using MALDI TOF technology), and a molecular assay for the detection of the major genes conferring resistance, all of them performed directly from positive BCs. The application of phylogenetic and phylodynamic analyses to bacterial whole-genome sequencing (WGS) data have become essential in the epidemiological surveillance of multidrug-resistant nosocomial pathogens. We analyzed 40 strains of Klebsiella pneumoniae subsp. pneumoniae (KP) carrying blaKPC (KP-KPC), randomly selected among 147 CPE identified from BCs collected from consecutive patients from 2013 to 2016. The number of BSIs-related CPE were 23, 31, 43, and 50 in 2013, 2014, 2015, and 2016, respectively. Among 147 CPE isolates, 143 were KP and four were Escherichia coli (EC). The gene blaKPC was detected in 117 strains of KP and in four strains of EC. Other carbapenemase genes, such as blaVIM and blaOXA-48, were detected in four and nine different isolates of KP, respectively. Moreover, 13 KP strains carried two resistance genes: twelve vehicled blaKPC plus blaVIM and one blaKPC plus blaOXA-48. Phylogenetic analysis of bacterial WGS data was used to investigate the evolution and spatial dispersion of KP in support of hospital infection control. The maximum likelihood tree showed two main clades statistically supported, with statistical support for several subclusters within as well. The minimum spanning tree showed mixing between sequences from different years and wards with only few specific groups. Bayesian analyses are ongoing, as the aid of Bayesian genomic epidemiology in combination with active microbial surveillance is highly informative regarding the development of effective infection prevention in healthcare settings or constant strain reintroduction.

Identification and Characterization of Genetic Determinants of Isoniazid and Rifampicin Resistance in Mycobacterium tuberculosis in Southern India

Drug-resistant tuberculosis (TB), one of the leading causes of death worldwide, arises mainly from spontaneous mutations in the genome of Mycobacterium tuberculosis. There is an urgent need to understand the mechanisms by which the mutations confer resistance in order to identify new drug targets and to design new drugs. Previous studies have reported numerous mutations that confer resistance to anti-TB drugs, but there has been little systematic analysis to understand their genetic background and the potential impacts on the drug target stability and/or interactions. Here, we report the analysis of whole-genome sequence data for 98 clinical M. tuberculosis isolates from a city in southern India. The collection was screened for phenotypic resistance and sequenced to mine the genetic mutations conferring resistance to isoniazid and rifampicin. The most frequent mutation among isoniazid and rifampicin isolates was S315T in katG and S450L in rpoB respectively. The impacts of mutations on protein stability, protein-protein interactions and protein-ligand interactions were analysed using both statistical and machine-learning approaches. Drug-resistant mutations were predicted not only to target active sites in an orthosteric manner, but also to act through allosteric mechanisms arising from distant sites, sometimes at the protein-protein interface.

Abstract 970: The mutational landscape of normal human endometrial epithelium

Abstract Human endometrium is a highly dynamic tissue that undergoes hundreds of cycles of breakdown, rapid repair and remodelling in response to the oscillating levels of oestrogen and progesterone during female reproductive years. The marked regenerative capacity of this tissue’s epithelial compartment is maintained by intra-glandular adult stem cells (ASCs) that reside within the stratum basalis which is retained during menstruation. Although the endometrial ASCs were first described over a decade ago, they remain poorly characterised in comparison to their counterparts in other tissues, such as the small and the large intestines. In particular, the size of the stem cell pool within individual glands, the rates of their division, and mutational landscape are largely unknown. In this study, we isolated 215 morphologically normal endometrial glands from women aged 19 to 81 using laser capture microscopy. Analysis of whole-genome sequencing data identified that the overwhelming majority of the glands were clonal cell populations, and thus originating from a single ASC. Somatic mutations were found to accumulate at a linear rate during adult life. Elevated body mass index (BMI), a well-recognised risk factor for endometrial cancer, accelerated the rate of mutation acquisition. Surprisingly, despite the heterogeneity in age, reproductive history and BMI in our cohort, we find relatively homogenous mutational processes within normal endometrium. Comparison with cancer, shows lower somatic mutation burden and fewer operative signatures. Remarkably, we not only identify recurrent acquisitions of certain cancer-associated mutations, particularly those that are advantageous to cell growth, proliferation and migration, but also show that such events occur early in life, potentially even before adolescence. Over time, these mutant ASCs serve as a reservoir for the acquisition of further driver mutations to the extent that in some cases, the entire sampled endometrium becomes ‘neoplastic’ on the genomic level while still retaining the apparently normal phenotype. In older individuals, we observe a shift in the spectrum of acquired cancer-associated mutations, possibly reflecting post-menopausal changes in the levels of sex-steroid hormones and the resultant tissue microenvironment. Citation Format: Luiza Moore, Daniel Leongamornlert, Tim Coorens, Mathijs Sanders, Peter Ellis, Francesco Maura, Kevin Dawson, Simon F. Brunner, Jyoti Nangalia, Henry Lee-Six, Raheleh Rahbari, Patrick Tarpey, Yvette Hooks, Krishnaa Mahbubani, Christine A. Iacobuzio-Donahue, Jan J. Brosens, Inigo Martincorena, Kourosh Saeb-Parsy, Peter J. Campbell, Michael R. Stratton. The mutational landscape of normal human endometrial epithelium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 970.

Abstract 4172: Identification of familial Hodgkin lymphoma predisposing genes by whole genome sequencing

Abstract Hodgkin lymphoma (HL) originates from germinal center B-cells and accounts for about 10% of newly diagnosed lymphomas and 1% of all de-novo neoplasms worldwide. Though familial risk for HL is among the highest of all cancers, not many genetic risk factors have been identified besides associations with the human leukocyte antigen (HLA) complex and few germline variants in familial classical Hodgkin lymphoma and nodular lymphocyte predominant Hodgkin lymphoma. With the aim of identifying novel predisposing germline variants in familial Hodgkin lymphoma, we performed whole genome sequencing (WGS) on seven affected and nine unaffected family members from three HL-prone families (families I, II and III). WGS identified a total of 98564, 170551 and 113654 variants in families I, II and III, respectively at ≤0.1% minor allele frequency. Variants were prioritized using the Familial Cancer Variant Prioritization Pipeline version 2 (FCVPPv2) developed by us. Pedigree-based filtering reduced the number of variants to 18158, 496 and 26851. Non-synonymous SNVs were the most represented exonic variants. Application of FCVPPv2 criteria resulted in prioritization of 19, 6 and 13 potentially causative exonic variants in families I, II and III, respectively. Variants affecting promoters, enhancers, super-enhancers, transcription factor binding sites and microRNA seed sequences were identified using FANTOM5 (Functional Annotation of the Mammalian Genome 5), SEA (Super-Enhancer Archive), SNPnexus and TargetScan tools. Pathway analysis of the involved genes using Ingenuity Pathway Analysis showed enrichment of B-cell receptor signaling, PI3K signaling in B lymphocytes and protein kinase A signaling pathways. Implementation of FCVPPv2 on data from family I resulted in confirmation and functional validation of a novel heterozygous missense variant (c.T5133G: p.I1711M) in the tumor suppressor gene DICER1 as potential HL predisposition factor. In order to identify the causal variants in families II and III, the variants short listed based on our pipeline are being investigated for segregation, frequency in large cohorts and functional consequences. In conclusion, WGS data analysis of three HL-prone families allowed us to prioritize coding and non-coding variants and identify enrichment of B-cell activating pathways. We aim to select and validate novel cancer predisposing variants that can facilitate genetic counseling and personalized therapy in these families as well as screening of other individuals at risk of developing Hodgkin lymphoma. Citation Format: Sara Giangiobbe, Aayushi Srivastava, Abhishek Kumar, Nagarajan Paramasivam, Dagmara Dymerska, Wolfgang Benisch, Mathias Witzens-Harig, Mathias Schlessner, Jan Lubinski, Kari Hemminki, Asta Försti, Obul R. Bandapalli. Identification of familial Hodgkin lymphoma predisposing genes by whole genome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4172.

Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

BackgroundMycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION.ResultsWe present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs.ConclusionsThe new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.

Phylogenetic Analysis of Mycobacterium tuberculosis Strains in Wales by Use of Core Genome Multilocus Sequence Typing To Analyze Whole-Genome Sequencing Data.

An inability to standardize the bioinformatic data produced by whole-genome sequencing (WGS) has been a barrier to its widespread use in tuberculosis phylogenetics. The aim of this study was to carry out a phylogenetic analysis of tuberculosis in Wales, United Kingdom, using Ridom SeqSphere software for core genome multilocus sequence typing (cgMLST) analysis of whole-genome sequencing data. The phylogenetics of tuberculosis in Wales have not previously been studied. Sixty-six Mycobacterium tuberculosis isolates (including 42 outbreak-associated isolates) from south Wales were sequenced using an Illumina platform. Isolates were assigned to principal genetic groups, single nucleotide polymorphism (SNP) cluster groups, lineages, and sublineages using SNP-calling protocols. WGS data were submitted to the Ridom SeqSphere software for cgMLST analysis and analyzed alongside 179 previously lineage-defined isolates. The data set was dominated by the Euro-American lineage, with the sublineage composition being dominated by T, X, and Haarlem family strains. The cgMLST analysis successfully assigned 58 isolates to major lineages, and the results were consistent with those obtained by traditional SNP mapping methods. In addition, the cgMLST scheme was used to resolve an outbreak of tuberculosis occurring in the region. This study supports the use of a cgMLST method for standardized phylogenetic assignment of tuberculosis isolates and for outbreak resolution and provides the first insight into Welsh tuberculosis phylogenetics, identifying the presence of the Haarlem sublineage commonly associated with virulent traits.

Potentiation of Phase Variation in Multiple Outer-Membrane Proteins During Spread of the Hyperinvasive Neisseria meningitidis Serogroup W ST-11 Lineage.

BackgroundSince 2009, increases in the incidence of invasive meningococcal disease have occurred in the United Kingdom due to a sublineage of the Neisseria meningitidis serogroup W ST-11 clonal complex (hereafter, the “original UK strain”). In 2013, a descendent substrain (hereafter, the “2013 strain”) became the dominant disease-causing variant. Multiple outer-membrane proteins of meningococci are subject to phase-variable switches in expression due to hypermutable simple-sequence repeats. We investigated whether alterations in phase-variable genes may have influenced the relative prevalence of the original UK and 2013 substrains, using multiple disease and carriage isolates.MethodsRepeat numbers were determined by either bioinformatics analysis of whole-genome sequencing data or polymerase chain reaction amplification and sizing of fragments from genomic DNA extracts. Immunoblotting and sequence-translation analysis was performed to identify expression states.ResultsSignificant increases in repeat numbers were detected between the original UK and 2013 strains in genes encoding PorA, NadA, and 2 Opa variants. Invasive and carriage isolates exhibited similar repeat numbers, but the absence of pilC gene expression was frequently associated with disease.ConclusionsElevated repeat numbers in outer-membrane protein genes of the 2013 strain are indicative of higher phase-variation rates, suggesting that rapid expansion of this strain was due to a heightened ability to evade host immune responses during transmission and asymptomatic carriage.

Whole-genome sequence analysis of a Pan African set of samples reveals archaic gene flow from an extinct basal population of modern humans into sub-Saharan populations

BackgroundPopulation demography and gene flow among African groups, as well as the putative archaic introgression of ancient hominins, have been poorly explored at the genome level.ResultsHere, we examine 15 African populations covering all major continental linguistic groups, ecosystems, and lifestyles within Africa through analysis of whole-genome sequence data of 21 individuals sequenced at deep coverage. We observe a remarkable correlation among genetic diversity and geographic distance, with the hunter-gatherer groups being more genetically differentiated and having larger effective population sizes throughout most modern-human history. Admixture signals are found between neighbor populations from both hunter-gatherer and agriculturalists groups, whereas North African individuals are closely related to Eurasian populations. Regarding archaic gene flow, we test six complex demographic models that consider recent admixture as well as archaic introgression. We identify the fingerprint of an archaic introgression event in the sub-Saharan populations included in the models (~ 4.0% in Khoisan, ~ 4.3% in Mbuti Pygmies, and ~ 5.8% in Mandenka) from an early divergent and currently extinct ghost modern human lineage.ConclusionThe present study represents an in-depth genomic analysis of a Pan African set of individuals, which emphasizes their complex relationships and demographic history at population level.

Germline deletion of ETV6 in familial acute lymphoblastic leukemia

AbstractRecent studies have identified germline mutations in TP53, PAX5, ETV6, and IKZF1 in kindreds with familial acute lymphoblastic leukemia (ALL), but the genetic basis of ALL in many kindreds is unknown despite mutational analysis of the exome. Here, we report a germline deletion of ETV6 identified by linkage and structural variant analysis of whole-genome sequencing data segregating in a kindred with thrombocytopenia, B-progenitor acute lymphoblastic leukemia, and diffuse large B-cell lymphoma. The 75-nt deletion removed the ETV6 exon 7 splice acceptor, resulting in exon skipping and protein truncation. The ETV6 deletion was also identified by optimal structural variant analysis of exome sequencing data. These findings identify a new mechanism of germline predisposition in ALL and implicate ETV6 germline variation in predisposition to lymphoma. Importantly, these data highlight the importance of germline structural variant analysis in the search for germline variants predisposing to familial leukemia.

UltraStrain: An NGS-Based Ultra Sensitive Strain Typing Method for Salmonella enterica.

In the last few years, advances in next-generation sequencing (NGS) technology for whole genome sequencing (WGS) of foodborne pathogens have provided drastic improvements in food pathogen outbreak surveillance. WGS of foodborne pathogen enables identification of pathogens from food or environmental samples, including difficult-to-detect pathogens in culture-negative infections. Compared to traditional low-resolution methods such as the pulsed-field gel electrophoresis (PFGE), WGS provides advantages to differentiate even closely related strains of the same species, thus enables rapid identification of food-source associated with pathogen outbreak events for a fast mitigation plan. In this paper, we present UltraStrain, which is a fast and ultra sensitive pathogen detection and strain typing method for Salmonella enterica (S. enterica) based on WGS data analysis. In the proposed method, a noise filtering step is first performed where the raw sequencing data are mapped to a synthetic species-specific reference genome generated from S. enterica specific marker sequences to avoid potential interference from closely related species for low spike samples. After that, a statistical learning based method is used to identify candidate strains, from a database of known S. enterica strains, that best explain the retained S. enterica specific reads.Finally, a refinement step is further performed by mapping all the reads before filtering onto the identified top candidate strains, and recalculating the probability of presence for each candidate strain. Experiment results using both synthetic and real sequencing data show that the proposed method is able to identify the correct S. enterica strains from low-spike samples, and outperforms several existing strain-typing methods in terms of sensitivity and accuracy.

Validation of a Bioinformatics Workflow for Routine Analysis of Whole-Genome Sequencing Data and Related Challenges for Pathogen Typing in a European National Reference Center: Neisseria meningitidis as a Proof-of-Concept.

Despite being a well-established research method, the use of whole-genome sequencing (WGS) for routine molecular typing and pathogen characterization remains a substantial challenge due to the required bioinformatics resources and/or expertise. Moreover, many national reference laboratories and centers, as well as other laboratories working under a quality system, require extensive validation to demonstrate that employed methods are “fit-for-purpose” and provide high-quality results. A harmonized framework with guidelines for the validation of WGS workflows does currently, however, not exist yet, despite several recent case studies highlighting the urgent need thereof. We present a validation strategy focusing specifically on the exhaustive characterization of the bioinformatics analysis of a WGS workflow designed to replace conventionally employed molecular typing methods for microbial isolates in a representative small-scale laboratory, using the pathogen Neisseria meningitidis as a proof-of-concept. We adapted several classically employed performance metrics specifically toward three different bioinformatics assays: resistance gene characterization (based on the ARG-ANNOT, ResFinder, CARD, and NDARO databases), several commonly employed typing schemas (including, among others, core genome multilocus sequence typing), and serogroup determination. We analyzed a core validation dataset of 67 well-characterized samples typed by means of classical genotypic and/or phenotypic methods that were sequenced in-house, allowing to evaluate repeatability, reproducibility, accuracy, precision, sensitivity, and specificity of the different bioinformatics assays. We also analyzed an extended validation dataset composed of publicly available WGS data for 64 samples by comparing results of the different bioinformatics assays against results obtained from commonly used bioinformatics tools. We demonstrate high performance, with values for all performance metrics >87%, >97%, and >90% for the resistance gene characterization, sequence typing, and serogroup determination assays, respectively, for both validation datasets. Our WGS workflow has been made publicly available as a “push-button” pipeline for Illumina data at https://galaxy.sciensano.be to showcase its implementation for non-profit and/or academic usage. Our validation strategy can be adapted to other WGS workflows for other pathogens of interest and demonstrates the added value and feasibility of employing WGS with the aim of being integrated into routine use in an applied public health setting.

Genome-wide analyses as part of the international FTLD-TDP whole-genome sequencing consortium reveals novel disease risk factors and increases support for immune dysfunction in FTLD.

Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) represents the most common pathological subtype of FTLD. We established the international FTLD-TDP whole-genome sequencing consortium to thoroughly characterize the known genetic causes of FTLD-TDP and identify novel genetic risk factors. Through the study of 1131 unrelated Caucasian patients, we estimated that C9orf72 repeat expansions and GRN loss-of-function mutations account for 25.5% and 13.9% of FTLD-TDP patients, respectively. Mutations in TBK1 (1.5%) and other known FTLD genes (1.4%) were rare, and the disease in 57.7% of FTLD-TDP patients was unexplained by the known FTLD genes. To unravel the contribution of common genetic factors to the FTLD-TDP etiology in these patients, we conducted a two-stage association study comprising the analysis of whole-genome sequencing data from 517 FTLD-TDP patients and 838 controls, followed by targeted genotyping of the most associated genomic loci in 119 additional FTLD-TDP patients and 1653 controls. We identified three genome-wide significant FTLD-TDP risk loci: one new locus at chromosome 7q36 within the DPP6 gene led by rs118113626 (p value = 4.82e-08, OR = 2.12), and two known loci: UNC13A, led by rs1297319 (p value = 1.27e-08, OR = 1.50) and HLA-DQA2 led by rs17219281 (p value = 3.22e-08, OR = 1.98). While HLA represents a locus previously implicated in clinical FTLD and related neurodegenerative disorders, the association signal in our study is independent from previously reported associations. Through inspection of our whole-genome sequence data for genes with an excess of rare loss-of-function variants in FTLD-TDP patients (n ≥ 3) as compared to controls (n = 0), we further discovered a possible role for genes functioning within the TBK1-related immune pathway (e.g., DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP. Together, our study based on the largest cohort of unrelated FTLD-TDP patients assembled to date provides a comprehensive view of the genetic landscape of FTLD-TDP, nominates novel FTLD-TDP risk loci, and strongly implicates the immune pathway in FTLD-TDP pathogenesis.