Isolate Sequencing Services for Infection Prevention and Control

Outbreak Surveillance and Infection Prevention require accurate typing and characterization of bacterial isolates. Sequence your isolates with the pathogenomics- and AMR-experts at Ares Genetics and rely on the validated, AI powered ARESiss platform for accurate, comprehensive, and epidemiologically relevant data from microbial isolates.

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Bacterial Isolates or DNA

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DNA Extraction

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Data Analysis & Interpretation

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Comprehensive Reporting

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Your Benefits

Accurate surveillance

Reduce antibiotic use

Monitor trends and identify the emergence of new threats

Trace chains of transmission

Improve antimicrobial therapy through predictive AST

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We Offer

Express services upon request (standard turn-around time of 4-6 weeks)

Quality results based on validated ARESiss platform1

Access to reports via the AREScloud portal

ARES Technology

The ARESiss platform has been validated end-to-end using CLIA-grade processes to ensure accurate and reproducible isolate sequencing results.2

For research use only and not for diagnostics purposes.

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Whole genome sequencing using short- or long-read technology

Pathogen Characterization
Typing (cgMLST, MLST)
AMR marker profiling & annotation

Data Analysis and Interpretation
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Advanced Interpretation (optional)
Outbreak analysis
Predictive AST
Custom analytics

Comprehensive Reporting
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Web portal for reports and interpretation

Ares Expertise

An industry leading database and AI powered bioinformatics platform convert isolate genome data into epidemiologically actionable information.

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ARESdb is a comprehensive collection of resistance-associated genes and genetic markers for AMR. ARESdb includes known biomarkers and novel ones identified by our proprietary AI discovery platform. Additionally, ARESdb holds an industry-leading set of curated antibiotic susceptibility profiles and associated genomic information, enabling predictive AST.2,3

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ARESai aims to set the Industry Standard for AI powered Infectious disease testing in accordance with FDA guidelines.4,5 Ares data analysis enables pathogen identification and antibiotic resistance detection with superior accuracy.6,7 The award-winning team of Ares data scientists has demonstrated superior accuracy in independent studies, including the first multi-center evaluation of NGS-based predictive AST.6,8

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AREScloud is a web-based, user-friendly portal to Isolate Reports and an interface enabling decentralized NGS-based Isolate Analysis for reference labs and medical centers.

  1. Lepuschitz, S. et al. Analytical Performance Validation of Next-Generation Sequencing Based Clinical Microbiology Assays Using a K-mer Analysis Workflow. Front Microbiol 11, 1883 2020
  2. Mahfouz, N. et al. Large-scale assessment of antimicrobial resistance marker databases for genetic phenotype prediction: a systematic review. J Antimicrob Chemoth 75, dkaa257- 2020
  3. Galata, V. et al. Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates. Genom Proteom Bioinform 17, 169–182 2019
  4. FDA, U. Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan 2021
  5. Lüftinger, L. et al. Learning From Limited Data: Towards Best Practice Techniques for Antimicrobial Resistance Prediction From Whole Genome Sequencing Data. Front Cell Infect Mi 11, 610348 2021
  6. Ferreira, I. et al. Species Identification and Antibiotic Resistance Prediction by Analysis of Whole Genome Sequence Data Using ARESdb – An Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial. Journal of clinical microbiology 2020 doi:10.1128/jcm.00273-20
  7. Reller, L. B. et al. Antimicrobial Susceptibility Testing: A Review of General Principles and Contemporary Practices. Clin Infect Dis 49, 1749–1755 2009
  8. Volz, C. et al. Clinical Resistome Screening of 1,110 Escherichia coli Isolates Efficiently Recovers Diagnostically Relevant Antibiotic Resistance Biomarkers and Potential Novel Resistance Mechanisms. Front Microbiol 10, 1671 2019