At Ares Genetics, we develop precision diagnostics for precision medicine to improve the way infections are diagnosed and treated.
We are data scientists, bioinformaticians, microbiologists, pharmaceutical, diagnostic and commercial experts that share a vision for the next-generation of genomics-based infectious disease diagnostics & therapeutics.
Join us in taking infectious disease diagnostics to the next level!
Besides the openings listed below, we are regularly offering part- or full-time positions as well as PhD and master theses and welcome unsolicitated applications.
At Ares, we pursue a partnership based, open-innovation approach with academic and industry partners and are committed to sharing our developments with the community.
The purpose of this multicenter validation study was to assess the performance of Oxford Nanopore Technologies (ONT) sequencing of bacterial isolates to enable fast, cost effective, and easily deployable genomic antimicrobial surveillance. To this end we validated end-to-end workflows for ONT sequencing and AREScloud for bioinformatics analysis. Pathogen identification was found to be 100% accurate and reproducible across extraction methods and labs. For AMR marker detection and predictive AST accuracies of up to 97% and a reproducibility across labs and protocols of 96% or higher were reached. Plasmid typing performed similarly well with an accuracy up to 90% and a reproducibility of consistently 100%. Summarizing, ONT sequencing together with AREScloud was found to enable accurate and robust genomic antimicrobial surveillance.
Joint publication with the Johns Hopkins University School of Medicine. As cefiderocol is increasingly being prescribed in clinical practice, it is critical to understand key mechanisms contributing to acquired resistance to this agent. This study reports on the case of a patient with acute lymphoblastic leukemia with an NDM-5 producing Escherichia coli intra-abdominal infection where resistance to cefiderocol evolved approximately 2 weeks after initiating cefiderocol therapy. Through WGS investigations, mRNA expression studies, and EDTA inhibition analysis, the role of increased NDM-5 production and genetic mutations contributing to the development of cefiderocol resistance was investigated using 5 sequential clinical E. coli isolates obtained from the patient. The patient’s case suggests that increased copy numbers of blaNDM genes through translocation events is used by Enterobacterales to evade cefiderocol-mediated cell death. The frequency of increased NDM expression in contributing to cefiderocol resistance needs investigation.
Joint publication with Johns Hopkins University School of Medicine. The objective of this study was to identify putative mechanisms contributing to baseline cefiderocol resistance among carbapenem-resistant Enterobacterales (CRE). 56 clinical CRE isolates with no previous exposure to cefiderocol were evaluated. Cefiderocol and comparator agent minimum inhibitory concentrations (MICs) were determined by broth microdilution. Short-read and/or long-read whole genome sequencing was pursued. Cefiderocol nonwild type (NWT; i.e., MICs ≥4 mg/L) CRE were compared with species-specific reference genomes and with cefiderocol wild type (WT) CRE isolates to identify genes or missense mutations, potentially contributing to elevated cefiderocol MICs. A total of 14 (25%) CRE isolates met cefiderocol NWT criteria. Of the 14 NWT isolates, various β-lactamases (e.g., carbapenemases in Klebsiella pneumoniae and AmpC β-lactamases in Enterobacter cloacae complex) in combination with permeability defects were associated with a ≥ 80% positive predictive value in identifying NWT isolates. Unique mutations in the sensor kinase gene baeS were identified among NWT isolates. Cefiderocol NWT isolates were more likely to be resistant to colistin than WT isolates (29% vs. 0%). The findings suggest that no consistent antimicrobial resistance markers contribute to baseline cefiderocol resistance in CRE isolates and, rather, cefiderocol resistance results from a combination of heterogeneous mechanisms.
Joint publication with the Mayo Clinic and Vanderbilt University. 50 Escherichia coli bloodstream isolates from the clinical laboratory and 12 E. coli isolates referred for PFGE were sequenced, assessed for clonality using cgMLST and evaluated for genomic susceptibility predictions using ARESdb. Sequence typing using WGS-based MLST and ST-specific PCR were identical. Overall categorical agreement between genotypic (ARESdb) and phenotypic susceptibility testing for 62 isolates and 11 antimicrobial agents was 91%. Among the referred isolates, high ceftazidime, cefepime, and piperacillin-tazobactam major error rates were found.
Joint Ares Genetics publication with the Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck and Michael Ogon Laboratory for Orthopaedic Research. The increasing incidence of antimicrobial resistance (AMR) is a major global challenge. Routine techniques for molecular AMR marker detection are largely based on low-plex PCR and detect dozens to hundreds of AMR markers. To allow for comprehensive and sensitive profiling of AMR markers, we developed a capture-based next generation sequencing (NGS) workflow featuring a novel AMR marker panel based on the curated AMR database ARESdb. Our primary objective was to compare the sensitivity of target enrichment-based AMR marker detection to metagenomics sequencing. Therefore, we determined the limit of detection (LOD) in synovial fluid and urine samples across four key pathogens. We further demonstrated proof-of-concept for AMR marker profiling from septic samples using a selection of urine samples with confirmed monoinfection. The results showed that the capture-based workflow is more sensitive and requires lower sequencing depth compared with metagenomics sequencing, allowing for comprehensive AMR marker detection with an LOD of 1000 CFU/mL. Combining the ARESdb AMR panel with 16S rRNA gene sequencing allowed for the culture-free detection of bacterial taxa and AMR markers directly from septic patient samples at an average sensitivity of 99%. Summarizing, the newly developed ARESdb AMR panel may serve as a valuable tool for comprehensive and sensitive AMR marker detection.
Joint Ares Genetics publication with the Michael Ogon Laboratory for Orthopaedic Research. Joint replacement surgeries are one of the most frequent medical interventions globally. Infections of prosthetic joints are a major health challenge and typically require prolonged or even indefinite antibiotic treatment. As multidrug-resistant pathogens continue to rise globally, novel diagnostics are critical to ensure appropriate treatment and help with prosthetic joint infections (PJI) management. To this end, recent studies have shown the potential of molecular methods such as next-generation sequencing to complement established phenotypic, culture-based methods. Together with advanced bioinformatics approaches, next-generation sequencing can provide comprehensive information on pathogen identity as well as antimicrobial susceptibility, potentially enabling rapid diagnosis and targeted therapy of PJIs. In this review, we summarize current developments in next generation sequencing based predictive antibiotic susceptibility testing and discuss potential and limitations for common PJI pathogens.
Joint Ares Genetics publication with Johns Hopkins University. Mutations in the AmpC-AmpR region are associated with treatment-emergent ceftolozane-tazobactam (TOL-TAZ) and ceftazidime-avibactam (CAZ-AVI) resistance. We sought to determine if these mutations impact susceptibility to the novel cephalosporin-siderophore compound cefiderocol.
Joint Ares Genetics publication with the Medical University of Innsbruck and the Danube University Krems. In this retrospective study, we investigated genetic resistance mechanisms, sequence types (ST) and respective phenotypes of linezolid-resistant Staphylococcus epidermidis (LRSE) recovered from a cohort of patients receiving or not receiving linezolid within a tertiary hospital in Innsbruck, Austria.
The work led by Ares Genetics and performed in collaboration with Prof. Thomas Rattei from the Division of Computational Systems Biology at the University of Vienna critically assessed different machine learning (ML) techniques for whole genome sequencing (WGS)-based AST on several thousand genome assemblies across more than 50 species/compound combinations collated from public databases. The publication describes the combination of different machine learning architectures for robust and accurate WGS-based AST.
This publication demonstrates applicability of k-mer based clinical microbiology assays for whole-genome sequencing (WGS) including variant calling, taxonomic identification, bacterial typing as well as AMR marker detection. The wet-lab and dry-lab workflows were developed and validated in line with Clinical Laboratory Improvement Act (CLIA) guidelines for laboratory-developed tests (LDTs) on multi-drug resistant ESKAPE pathogens.
Have you ever wondered how rapidly resistance develops against new antibiotics? Unfortunately, very soon after their introduction into clinic. Have you ever wondered about the number of infections that cannot be treated with existing antibiotics? Luckily only very few, in fact less than 0.1%. The world is on the verge of losing antibiotics as its most powerful tool in healthcare. Read our whitepaper why new antibiotics won’t solve the antibiotic resistance crisis, but better diagnostics could.
Multi-center US study demonstrating feasibility and potential of next-generation sequencing based antibiotic susceptibility prediction using ares-genetics.cloud. The study evaluated the performance of pathogen identification and antibiotic susceptibility testing based on whole genome DNA sequencing (WGS) using Ares Genetics’ AI-powered cloud-based bioinformatics platform and the underlying reference database, ARESdb. WGS-predicted susceptibility to antibiotics showed 89% categorical agreement with the current reference method of broth microdilution susceptibility testing across a total of 129 pathogen-drug pairs analyzed. Categorical agreement exceeded 90% in 78, and reached 100% in 32 pathogen drug pairs.
Joint Ares Genetics publication with Prof. Müller (HIPS Saarbrücken) and Prof. Keller (CCB Saarland). The study introduces a novel, universally applicable high-throughput workflow for rapid identification and functional validation of antimicrobial resistance (AMR) biomarkers from >1,000 clinical isolates. When combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached high positive and negative predictive values of up to 97 and 99%, respectively. Additionally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms.
Joint Ares Genetics publication with Prof. Keller’s group at Saarland University introducing GEAR-base as a standardized research resource for antibiotic resistance genotypes and phenotypes. GEAR-base was originally established in collaboration with Universität des Saarlandes and Siemens and forms the nucleus of our proprietary ARESdb now combining whole-genome sequencing data for > 35,000 isolates with quantitative antibiotic susceptibility data for >100 antibiotics..
Joint Ares Genetics publication with Prof. Keller’s group at Saarland University assessing the heterogeneity of in silico plasmid predictions based on whole-genome-sequenced clinical isolates. The study identified a high degree of heterogeneity and variation in sensitivity and precision for plasmid identification across taxa and computational approaches. Nevertheless, existing open source tools are very valuable for investigating the plasmid-borne resistome. Building upon the peer-reviewed research findings, the proprietary ARES Technology allows for fast and optimized plasmid identification from whole-genome sequencing data.
We offer a comprehensive portfolio of solutions for antimicrobial drug discovery, clinical development, and product lifecycle management. Our solutions aim at supporting data-driven target and lead prioritization, accelerating clinical trials, augmenting clinical data for regulatory submissions, and informed antimicrobial drug use for effective antibiotic stewardship post launch.
Joint Ares Genetics publication with Prof. Keller’s group at Saarland University comparing genome versus proteome-based identification of clinical bacterial isolates. Key findings include that taxonomic identification based on the proteome (by mass spectrometry, MS-biotyping) and the genome (by next-generation sequencing, NGS) show high concordance for clinical application. While NGS successfully resolved all clinical isolates on the species level, for 12% of the cases MS-biotyping resulted in genus level classification only. Building upon the peer-reviewed research findings, ARES Technology allows for fast and accurate taxonomic identification on the species level.