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Staphylococcus aureus biofilm is a common bio-contaminant source that leads to food cross-contamination and foodborne disease outbreaks. Hence, there is a need for searching novel antibiofilm agents with potential anti-virulence properties to control S. aureus contamination and infections in food systems. In this study, the antibiofilm effects of lactobionic acid (LBA) against S. aureus and its influence on virulence were explored. The minimum inhibition concentration of LBA on S. aureus was 8 mg/mL. Viable count and crystal violet assays revealed that LBA inhibited and inactivated S. aureus biofilms. Microscopic observations further confirmed the antibiofilm activity of LBA on S. aureus that disrupted the biofilm architecture and inactivated the viable cells in biofilms. Moreover, LBA decreased the release of extracellular DNA (eDNA) and extracellular polysaccharide (EPS) in S. aureus biofilms. LBA suppressed biofilm formation by intervening metabolic activity and reduced virulence secretion by repressing the hemolytic activity of S. aureus. Furthermore, LBA altered the expressions of biofilm- and virulence-related genes in S. aureus, further confirming that LBA suppressed biofilm formation and reduced the virulence secretion of S. aureus. The results suggest that LBA might be useful in preventing and controlling biofilm formation and the virulence of S. aureus to ensure food safety. [ABSTRACT FROM AUTHOR]

Translating RNA-seq into clinical diagnostics requires ensuring the reliability and cross-laboratory consistency of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. As part of the Quartet project, we present an RNA-seq benchmarking study across 45 laboratories using the Quartet and MAQC reference samples spiked with ERCC controls. Based on multiple types of ‘ground truth’, we systematically assess the real-world RNA-seq performance and investigate the influencing factors involved in 26 experimental processes and 140 bioinformatics pipelines. Here we show greater inter-laboratory variations in detecting subtle differential expressions among the Quartet samples. Experimental factors including mRNA enrichment and strandedness, and each bioinformatics step, emerge as primary sources of variations in gene expression. We underscore the profound influence of experimental execution, and provide best practice recommendations for experimental designs, strategies for filtering low-expression genes, and the optimal gene annotation and analysis pipelines. In summary, this study lays the foundation for developing and quality control of RNA-seq for clinical diagnostic purposes.Here the authors report on an RNA-seq benchmarking study that demonstrates greater inter-lab variations in detecting subtle differential expression. The study reveals the impact of experimental execution, experimental designs, low-expression gene filtering, and analysis tool selection. [ABSTRACT FROM AUTHOR]

Accurate indel calling plays an important role in precision medicine. A benchmarking indel set is essential for thoroughly evaluating the indel calling performance of bioinformatics pipelines. A reference sample with a set of known-positive variants was developed in the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, but the known indels in the known-positive set were limited. This project sought to provide an enriched set of known indels that would be more translationally relevant by focusing on additional cancer related regions. A thorough manual review process completed by 42 reviewers, two advisors, and a judging panel of three researchers significantly enriched the known indel set by an additional 516 indels. The extended benchmarking indel set has a large range of variant allele frequencies (VAFs), with 87% of them having a VAF below 20% in reference Sample A. The reference Sample A and the indel set can be used for comprehensive benchmarking of indel calling across a wider range of VAF values in the lower range. Indel length was also variable, but the majority were under 10 base pairs (bps). Most of the indels were within coding regions, with the remainder in the gene regulatory regions. Although high confidence can be derived from the robust study design and meticulous human review, this extensive indel set has not undergone orthogonal validation. The extended benchmarking indel set, along with the indels in the previously published known-positive set, was the truth set used to benchmark indel calling pipelines in a community challenge hosted on the precisionFDA platform. This benchmarking indel set and reference samples can be utilized for a comprehensive evaluation of indel calling pipelines. Additionally, the insights and solutions obtained during the manual review process can aid in improving the performance of these pipelines., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)