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Microbial Resequencing and Profiling

Use microbial resequencing and profiling to:
  • Check or validate mutations on the genome level
  • Validate your bacterial production stem
  • Characterize microbial isolates by MLST



Considerations before starting a microbial resequencing project:

  • Is there a reference genome?
  • Is there a MLST profile?
  • Are larger modifications expected?
  • May a substatial DNA contamination occur?

Let us guide you – from design to analysis

Example projects using microbial resequencing:

  • Detect the pathogenetiy of Bacterial DNA isolates by MLST
  • Verify/detect SNPS and InDels
  • Check fort he specificity of an introduced mutation

Applications related to microbial resequencing:

  • Amplicon Metagenomics
  • De novo sequencing
  • Plasmid sequencing


A typical workflow for a microbial resequencing and profiling project is shown in the graphic below. Please note that our highly-modular processes allow you various entry and opting out options. If you outsource your entire NGS project to Microsynth or only parts of it is up to you.
For further reading and a detailed technical description, please download our Application Note Illumina Microbial Resequencing and profiling (see related downloads).


In bacterial resequencing studies a bacterial strain is sequenced and compared against the sequence of a reference strain. Our bacterial resequencing analysis module helps you to answer the following questions:

  1. How high is the sequencing coverage for the resequenced genome? (see Figure 1)
  2. What differences in the genomic structure such as single nucleotide variations (SNVs) or small insertions and deletions (InDels) are present and what is their position within the genome? (see Table 1)
  3. How do the observed mutations affect annotated genes and the corresponding protein sequence? (see Table 2)
Figure 1: Genome coverage histogram.
Table 1: Summary table for observed SNVs and InDels in the analyzed samples including the type of mutation (silent vs. non-silent). Differences in numbers are due to variations in non-coding or not annotated genomic regions or already reported isoforms.

Table 2: Table displaying detailed information on each observed variation like variant type and position, affected protein including reference and altered sequence.