A WGS infection control workflow with 1928

WGS is the gold standard (https://www.cdc.gov/pulsenet/pathogens/wgs.html) for determining relatedness between two samples. Together with the discriminatory power of WGS and the context from metadata, the 1928 platform adds an increased resolution and understanding of the transmission pathways in the hospital.

Sample Source

  • Environmental
  • Screening
  • Clinical

Culture

  • Sample isolate from any bacteria

Sequence

  • Independent of sequencing platform

1928

  • Confirm transmission
  • Determine severity
  • Contextualize transmissions by adding metadata
  • Report and communicate
  • Build your own library of sequence references

All species bioinformatic analysis
service in the cloud for bacterial DNA sequences

Analysis includes:

  • Quality control including sample quality
  • Automatic species identification
  • cgMLST for the most common HAI pathogens
  • SNP for all species
  • Resistance and virulence markers
  • Epidemiological metadata

Reliability & Validity

All analysis pipelines are validated and benchmarked against public reference databases and in cooperation with regional and international collaborators.

Security & Privacy

  • HIPAA & GDPR compliant
  • Hosted in an infrastructure compliant with ISO 27001

Best-in-class

1928’s analysis of WGS provides the highest discriminatory power for typing of pathogens.

Predictable Costs

Downstream analysis cost is fixed and easily predicted = improved control of cost of operations.

The 1928 Team is standing by
for the Bioinformatics Analysis

Bioinformatic and technical support include:

  • Active monitoring by 1928 team to ensure a complete relevant analysis
  • Hospital organization configuration for access to user accounts, units and sharing groups
  • General training in the service and analysis for all users in the platform
  • Assistance with technical evaluation of results

Our CTO Fredrik Dyrkell
about the 1928 platform

Cloud service platform for microbial analysis

1928 is a cloud-based service that analyzes resistance markers in bacteria from whole genome sequences (WGS). Our technology searches for resistance markers within the bacteria and performs relational analysis between samples.

From raw reads to result in minutes

You start by uploading the sample to our cloud-based platform and the analysis starts automatically. Your NGS raw data is transcribed to results, providing an understanding of both what is unique in the sample and the overall picture in between samples.

Start today

Several hospitals in Europe and the USA are already now getting value out of the 1928 service. So, if you are starting to do WGS, we will be happy to provide the analysis for you.

Methodology

Antibiotic resistance profiling and
virulence factor detection

The 1928 service contains well-validated and specially adapted algorithms that process the raw data file from the sequencing machine. By optimising data handling processes in the cloud, our calculations are always efficient and fast due to optimised workflows and use of distributed systems. The processed data is matched to our databases of genetic markers (genes and mutations) coding for antibiotic resistance or virulence factors. The database entries are collected from peer reviewed scientific journals and comprise clinically relevant markers that are carefully selected and manually curated. The result is delivered on the 1928 platform in an informative format and can also be exported.

Epidemiologic typing

The 1928 platform uses core genome multilocus sequence typing (cgMLST) for outbreak tracing. This method is robust and enables strong comparability between sample sets. We generate our own cgMLST schemes which consists of conserved genes that can be used to generate a "bacterial fingerprint". By visualising the number of identical genes found in phylogenetic trees, large sample sets can be compared and groups of closely related samples can be identified as outbreaks. The method also allows for new samples to be compared to historical data previously uploaded.