Microbes are among our planet's most ubiquitous organisms. They are present in every biosphere, including some of the most extreme locations on Earth. Microbes, in general, possess genomes much smaller in size compared to plants and animals, which makes them ideal for genetic and physiological studies.
Microbial genomics is largely the identification and characterization of their genetic compositions. The ability to process and analyze the genomic data collected from microbial organisms is a cornerstone of modern bioinformatics. Its broad applications cover every sector of our lives, such as ensuring safety of the food supply, maintaining human health and wellness, countering the spread of disease, and protecting the environment.
With bioinformatics tools developed and in place, Noblis can analyze all aspects of microbial genomics. We can identify organisms, assess microbial populations in environmental niches, catalogue evolutionary pathways, and define genetic relatedness between microbial strains, Furthermore, research is under way to explore the potential of using genomic traits to ascertain antibiotic resistance and virulence.
Learn how Noblis plays an active role in pushing the speed and accuracy of microbial genomic analysis forward:
Whole genome sequencing of uncultured samples directly from the environment or from a host—such as the human microbiome—provide rich datasets that are not attainable from traditional identification and characterization testing. Until recently, analysis of genomic populations—metagenomics—has been performed with the widely-used tool BLAST. Because its algorithm is heuristic, BLAST analysis does not always provide optimal alignment for sequences. Using BioVelocity, Noblis offers an unbiased and deterministic view of metagenomic data while maintaining speed. Metagenomic analysis can be used for:
Antibiotic resistance (ABR) is a growing national and international concern. An estimated 700,000 people will perish in the next year (2018) due to infection and complications from resistant organisms; some estimates project a rise to 10 million per year by 2050. Identifying the causative agent of disease and rapidly and accurately assessing its antibiotic resistance traits continues to be an intricate and time-consuming process.
Similar to our approach in detecting bacterial serotypes, Noblis is constructing a database of genes and sequences known to have or to be associated with ABR. We query genome sequence data of interest against the entire set to determine the identity and to see whether resistance genes or sequences of high similarity are present or absent. We have developed the expertise needed to:
Bacteria become pathogenic due to the presence of virulence factors, which are often obtained by genetic transfer with other organisms. In many cases, the pathogenic strains are very closely related—if not virtually identical—to their non-pathogenic neighbors. Virulence factors also play an important role in threat characterization and convey the necessary precautions for protection. Noblis’ virulence factors detection capabilities include:
High-throughput experiments generate large, heterogeneous data sets that are difficult to interpret. Properly constructed visualizations (e.g., heat maps, graphs) help researchers and practitioners interpret the results and continue with further data processing. The goal of Noblis’ visualizations is to generate meaningful, information-dense—but readable—representations with publication quality.
Noblis has also developed expertise with phylogenetic visualization and analysis to assist in the examination of the origin and evolution of contamination and outbreaks. When large numbers of organisms are compared, phylogenetic methods help us to create new evolutionary models based on the evolutionary processes revealed by the comparison. These models are useful to predict whether samples from an outbreak are a slight variation of, the same as, or a completely new form of an organism.
Noblis uses a variety of programming languages and tools to create customized, interactive figures, augmented with useful metadata. As examples, Noblis develops data maps for:
The NIH Antimicrobial Resistance Diagnostic Challenge