Genomic screening of cancer patients for predisposing variants is traditionally based on age at onset, family history and type of cancer. Whereas the clinical guidelines have proven efficient in identifying families exhibiting classical attributes of hereditary cancer, the frequency of patients with alternative presentations is unclear. We identified and characterized germline variants in 636 patients with advanced solid cancer using whole exome sequencing. Pathogenic and likely pathogenic germline variants among 168 genes associated with hereditary cancer were considered. These variants were identified in 17.8% of the patients and within a wide range of cancer types. In particular, patients with mesothelioma, ovarian cancer, cervical cancer, urothelial cancer, and cancer of unknown primary origin displayed high frequencies of pathogenic variants. Variants were predominantly found in DNA-repair pathways and about half were within genes involved in homologous recombination repair. Twenty-two BRCA1 and BRCA2 germline variants were identified in 12 different cancer types, of which 10 (45%) were not previously identified in these patients based on the current clinical guidelines. Loss of heterozygosity and somatic second hits were identified in several of the affected genes, supporting possible causality for cancer development. A potential treatment target based on the pathogenic germline variant could be suggested in 25 patients (4%). The study demonstrates a high frequency of pathogenic germline variants in the homologous recombination pathway in patients with advanced solid cancers. We infer that genetic screening in this group of patients may reveal high-risk families and identify patients with potential PARP inhibitor sensitive tumors.
Achromobacter species are increasingly being detected in patients with cystic fibrosis (CF), and this emerging pathogen is associated with antibiotic resistance and more severe disease outcomes. Nonetheless, little is known about the extent of transmission and antibiotic resistance development in Achromobacter infections. We sequenced the genomes of 101 clinical isolates of Achromobacter (A. xylosoxidans based on MALDI-TOF/API N20 typing) collected from 51 patients with CF—the largest longitudinal dataset to-date. We performed phylogenetic analysis on the genomes and combined this with epidemiological and antibiotic resistance data to identify patient-to-patient transmission and development of antibiotic resistance. We confirmed that MALDI-TOF/API N20 was not sufficient for Achromobacter species-level typing, and that the population of Achromobacter isolates was composed of five different species where A. xylosoxidans accounted for 52% of infections. Most patients were infected by unique Achromobacter clone types; nonetheless, suspected patient-to-patient transmission cases identified by shared clone types were observed in 35% (N=18) of patients. In 15 of 16 cases the suspected transmissions were further supported by genome- or clinic visit-based epidemiological analysis. Finally, we found that resistance developed over time. We show that whole-genome sequencing (WGS) is essential for Achromobacter species typing and patient-to-patient transmission identification which was identified in A. ruhlandii, A. xylosoxidans and, for the first time, A. insuavis. Furthermore, we show that the development of antibiotic resistance is associated with chronic Achromobacter infections. Our findings emphasize that transmission and antibiotic resistance should be considered in future treatment strategies.
Distinct SARS-CoV-2 lineages, discovered through various genomic surveillance initiatives, have emerged during the pandemic following unprecedented reductions in worldwide human mobility. We here describe a SARS-CoV-2 lineage - designated B.1.620 - discovered in Lithuania and carrying many mutations and deletions in the spike protein shared with widespread variants of concern (VOCs), including E484K, S477N and deletions HV69Δ, Y144Δ, and LLA241/243Δ. As well as documenting the suite of mutations this lineage carries, we also describe its potential to be resistant to neutralising antibodies, accompanying travel histories for a subset of European cases, evidence of local B.1.620 transmission in Europe with a focus on Lithuania, and significance of its prevalence in Central Africa owing to recent genome sequencing efforts there. We make a case for its likely Central African origin using advanced phylogeographic inference methodologies incorporating recorded travel histories of infected travellers.
Copy-number variations (CNVs) have important clinical implications for several diseases and cancers. Relevant CNVs are hard to detect because common structural variations define large parts of the human genome. CNV calling from short-read sequencing would allow single protocol full genomic profiling. We reviewed 50 popular CNV calling tools and included 11 tools for benchmarking in a reference cohort encompassing 39 whole genome sequencing (WGS) samples paired current clinical standard—SNP-array based CNV calling. Additionally, for nine samples we also performed whole exome sequencing (WES), to address the effect of sequencing protocol on CNV calling. Furthermore, we included Gold Standard reference sample NA12878, and tested 12 samples with CNVs confirmed by multiplex ligation-dependent probe amplification (MLPA). Tool performance varied greatly in the number of called CNVs and bias for CNV lengths. Some tools had near-perfect recall of CNVs from arrays for some samples, but poor precision. Several tools had better performance for NA12878, which could be a result of overfitting. We suggest combining the best tools also based on different methodologies: GATK gCNV, Lumpy, DELLY, and cn.MOPS. Reducing the total number of called variants could potentially be assisted by the use of background panels for filtering of frequently called variants.
Background Bacterial gene loss and acquisition is a well-known phenomenon which contributes to bacterial adaptation through changes in important phenotypes such as virulence, antibiotic resistance and metabolic capability. While advances in DNA sequencing have accelerated our ability to generate short genome sequence reads to disentangle phenotypic changes caused by gene loss and acquisition, the short-read genome sequencing often results in fragmented genome assemblies as a basis for identification of gene loss and acquisition events. However, sensitive and precise determination of gene content change for fragmented genome assemblies remains challenging as analysis needs to account for cases when only a fragment of the gene is assembled or when the gene assembly is split in more than one contig. Results We developed GenAPI, a command-line tool that is designed to compare the gene content of bacterial genomes for which only fragmented genome assemblies are available. GenAPI, unlike other available tools of similar purpose, accounts for imperfections in sequencing and assembly, and aims to compensate for them. We tested the performance of GenAPI on three different datasets to show that GenAPI has a high sensitivity while it maintains precision when dealing with partly assembled genes in both simulated and real datasets. Furthermore, we benchmarked the performance of GenAPI with six popular tools for gene presence-absence identification. Conclusions Our developed bioinformatics tool, called GenAPI, has the same precision and recall rates when analyzing complete genome sequences as the other tools of the same purpose; however, GenAPI’s performance is markedly better on fragmented genome assemblies.
Achromobacter species are increasingly being detected in patients with cystic fibrosis (CF), and this emerging pathogen has been associated with antibiotic resistance and more severe disease outcomes. Nonetheless, little is known about the extent of transmission and genetic adaptation in Achromobacter infections. We sequenced the genomes of 101 clinical isolates of Achromobacter collected from 51 patients with CF−the largest longitudinal dataset to-date. We performed a comprehensive pathogenomic analysis to identify pathogen population structure, within-host adaptation, mutational signatures, patient-to-patient transmission events, and associated genetic variation with antibiotic resistance phenotypes. We found that the population of Achromobacter isolates was composed of five different species where A. xylosoxidans accounted for 52% of the infections. Most patients were infected by unique Achromobacter clone types; nonetheless, patient-to-patient transmission events identified by shared clone types were observed in 35% (N=18) of patients. We found that the same regulatory and inorganic ion transport genes were frequently mutated in persisting clone types within and between species indicating convergent genetic adaptation. Genome-wide association study (GWAS) of six antibiotic resistance phenotypes revealed that the majority of associated genes were involved in transcription and inorganic ion transport. Overall, we provide insight into pathogenomics of chronic Achromobacter infections and show the relevance of whole genome sequencing of clinical isolates. Our findings on evolution and genetic adaptation can facilitate the understanding of disease progression, inform antibiotic treatment, and identify patient-to-patient transmission.
Genome analyses have documented that there are differences in gene repertoire between evolutionary distant lineages of the same bacterial species; however, less is known about microevolutionary dynamics of gene loss and acquisition within bacterial lineages as they evolve over years. Here, we analyzed the genomes of 45 Pseudomonas aeruginosa lineages evolving in the lungs of cystic fibrosis (CF) patients to identify genes that are lost or acquired during the first years of infection. On average, lineage genome content changed by 88 genes (range, 0 to 473). Genes were more often lost than acquired, and prophage genes were more variable than bacterial genes. We identified convergent loss or acquisition of the same genes across lineages, suggesting selection for loss and acquisition of certain genes in the host environment. We found that a notable proportion of such genes are associated with virulence; a trait previously shown to be important for adaptation. Furthermore, we also compared the genomes across lineages to show that the within-lineage variable genes (i.e., genes that had been lost or acquired during the infection) often belonged to genomic content not shared across all lineages. In sum, our analysis adds to the knowledge on the pace and drivers of gene loss and acquisition in bacteria evolving over years in a human host environment and provides a basis to further understand how gene loss and acquisition play roles in lineage differentiation and host adaptation. IMPORTANCE Bacterial airway infections, predominantly caused by P. aeruginosa, are a major cause of mortality and morbidity of CF patients. While short insertions and deletions as well as point mutations occurring during infection are well studied, there is a lack of understanding of how gene loss and acquisition play roles in bacterial adaptation to the human airways. Here, we investigated P. aeruginosa within-host evolution with regard to gene loss and acquisition. We show that during long-term infection P. aeruginosa genomes tend to lose genes, in particular, genes related to virulence. This adaptive strategy allows reduction of the genome size and evasion of the host’s immune response. This knowledge is crucial to understand the basic mutational steps that, on the timescale of years, diversify lineages and adds to the identification of bacterial genetic determinants that have implications for CF disease.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.