Industries · Infectious Diseases & Microbiome
Infectious Diseases & Microbiome
Multi-omics characterisation of pathogens, host response and microbial ecosystems.
Industries · Infectious Diseases & Microbiome
Multi-omics characterisation of pathogens, host response and microbial ecosystems.
Infection is not a single molecular event. The pathogen evolves, the host responds, and the surrounding microbial community shifts with disease progression or treatment. Measuring one side of that tells you less than measuring all three on the same samples.
Want to know how a treatment, a diet or an infection reshapes a microbial community? From sampling to interpretation, Microbiome Xplorer shows which communities change, which functions they carry, and how the host responds. Gut, skin, respiratory and other biological matrices.
Whole-genome and targeted sequencing for strain and lineage characterisation, variant profiling, phylogenetic relationships and resistance-associated variants. Across timepoints, the same framework tracks how a pathogen population changes under treatment pressure.
16S for community composition, diversity and differential abundance. Shotgun metagenomics where the question needs functional potential, strain-level resolution or low-abundance populations. Sequencing depth is set by the question and the sample complexity, not by a default.
Resistance determinants identified from shotgun data and, where a specific marker matters, monitored by targeted assays across the cohort.
Bulk RNA-seq for the transcriptional changes associated with infection, severity, progression or treatment response, with differential expression reported at gene and pathway level.
Metatranscriptomics where both responses have to be read from the same material, so the pathogen’s activity and the host’s reaction are measured on one sample rather than inferred from two.
Protein-level quantification by mass spectrometry, including TIMS-TOF workflows, matched against the transcriptomic result. Transcript and protein levels diverge often enough that agreement between them is informative in itself.
Molecular measurements set against severity, treatment, sampling timepoint, outcome and patient characteristics, which is what separates a signal associated with infection from one associated with how sick the patient already was.
Molecular signatures associated with severity, progression, treatment response or failure. Where independent cohorts exist, candidates are tested on data that did not contribute to finding them.
Tool versions, parameters, filtering criteria and statistical thresholds for every step. QC per sample and per cohort, with exclusions stated and justified. Interpretation written against the question the study started from. Processed matrices, result tables, versioned pipelines and figures, delivered for review or reproduction by a third party.
The laboratory work behind these analyses runs on OMICS4, GenXMap’s platform site, with sample requirements, logistics and turnaround defined per study.
The analysis does not have to start there. Transcriptomics, proteomics, metabolomics, microbiome or extracellular-vesicle data from an earlier study, an internal programme or another provider can be analysed on its own terms. What determines the analysis is the biological question, the study design and the metadata available.
Where several layers are available, we integrate them to find converging signals, separate robust effects from technical or donor variability, and build the evidence around the claim.
Book infectious disease platforms on OMICS4Case studies for this industry are in preparation: get in touch to discuss a project directly.
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