Benchmarking UMI-aware and standard variant callers for low frequency ctDNA variant detection.

BACKGROUND: Circulating tumour DNA (ctDNA) is a subset of cell free DNA (cfDNA) released by tumour cells into the bloodstream. Circulating tumour DNA has shown great potential as a biomarker to inform treatment in cancer patients. Collecting ctDNA is minimally invasive and reflects the entire genetic makeup of a patient's cancer. ctDNA variants in NGS data can be difficult to distinguish from sequencing and PCR artefacts due to low abundance, particularly in the early stages of cancer. Unique Molecular Identifiers (UMIs) are short sequences ligated to the sequencing library before amplification. These sequences are useful for filtering out low frequency artefacts. The utility of ctDNA as a cancer biomarker depends on accurate detection of cancer variants. RESULTS: In this study, we benchmarked six variant calling tools, including two UMI-aware callers for their ability to call ctDNA variants. The standard variant callers tested included Mutect2, bcftools, LoFreq and FreeBayes. The UMI-aware variant callers benchmarked were UMI-VarCal and UMIErrorCorrect. We used both datasets with known variants spiked in at low frequencies, and datasets containing ctDNA, and generated synthetic UMI sequences for these datasets. Variant callers displayed different preferences for sensitivity and specificity. Mutect2 showed high sensitivity, while returning more privately called variants than any other caller in data without synthetic UMIs - an indicator of false positive variant discovery. In data encoded with synthetic UMIs, UMI-VarCal detected fewer putative false positive variants than all other callers in synthetic datasets. Mutect2 showed a balance between high sensitivity and specificity in data encoded with synthetic UMIs. CONCLUSIONS: Our results indicate UMI-aware variant callers have potential to improve sensitivity and specificity in calling low frequency ctDNA variants over standard variant calling tools. There is a growing need for further development of UMI-aware variant calling tools if effective early detection methods for cancer using ctDNA samples are to be realised.

Exopolymeric substances (EPS) from Salmonella enterica: polymers, proteins and their interactions with plants and abiotic surfaces.

When Salmonella enterica is not in a planktonic state, it persists in organised communities encased in extracellular polymeric substances (EPS), defined as biofilms. Environmental conditions ultimately dictate the key properties of the biofilms such as porosity, density, water content, charge, sorption and ion exchange properties, hydrophobicity and mechanical stability. S. enterica has been extensively studied due to its ability to infect the gastrointestinal environment. However, only during the last decades studies on its persistence and replication in soil, plant and abiotic surfaces have been proposed. S. enterica is an environmental bacterium able to effectively persist outside the human host. It does so by using EPS as tools to cope with environmental fluctuations. We therefore address this mini-review to classify those EPS that are produced by Salmonella with focus on the environment (plant, soil, and abiotic surfaces) by using a classification of EPS proposed by Flemming and collaborators in 2007. The EPS are therefore classified as structural, sorptive, surface-active, active, and informative.