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Zhijun Zhang

Publications and source records attributed to Zhijun Zhang.

2 recordsLinked to original sources

MultiDMPcaller: a one-stop software for detection and visualization of differentially methylated positions and regions.

MOTIVATION: Whole-genome bisulfite sequencing (WGBS/BS-Seq) is the gold standard for single-base resolution DNA methylome profiling. However, the diverse statistical models of existing computational methods lead to limited overlap between their results, highlighting the need for novel methods to detect differentially methylated positions (DMPs) and differentially methylated regions (DMRs). RESULTS: We developed MultiDMPcaller, an automated downstream methylome analysis software. It processes upstream outputs to profile DMPs, non-DMPs, DMRs, and context-specific (CpG/CHG/CHH) methylation status, alongside visualizing their chromosomal distribution and enrichment. The software features two key innovations: (i) an adaptive two-step P-value adjustment strategy based on organism-specific methylation patterns, with raw P-value ≤0.05 pre-filtering followed by false discovery rate (FDR) correction, to recover potential DMPs usually missed by standard FDR correction in plant CHG/CHH and animal CpG contexts; and (ii) a multiple pairwise comparison approach, which performs m × n pairwise comparisons for m control and n experimental replicates, followed by a voting system supporting both user-defined majority thresholds and model-based adaptive thresholds, to identify robust and reliable DMPs (with a stricter voting threshold exclusively for loci with low methylation differences) and DMRs. On real datasets from Arabidopsis, apple, and mouse, as well as simulated human datasets, MultiDMPcaller's results showed good agreement with those of other software, exhibiting high conservativeness and superior precision, which suggested a low false discovery proportion. AVAILABILITY AND IMPLEMENTATION: MultiDMPcaller is available at GitHub (https://github.com/jiantaoyuNWAFU/MultiDMPcaller) and via a web server (https://ciebioinfo.nwafu.edu.cn).

Software

Genetic characterization of carbapenem-resistant Klebsiella pneumoniae bloodstream isolates with reduced susceptibility to cefiderocol.

OBJECTIVES: To assess cefiderocol activity against carbapenem-resistant Klebsiella pneumoniae (CRKP) bloodstream isolates collected before local clinical introduction and to characterize the distribution of borderline MIC elevation across major genomic backgrounds. METHODS: We retrospectively analyzed 389 episodes of K. pneumoniae bloodstream infection at a tertiary hospital in China during 2018-2024. All 83 carbapenem-resistant isolates underwent cefiderocol broth microdilution testing and whole-genome sequencing. For epidemiological analysis, reduced susceptibility was prespecified as an MIC of 4-16 mg/L and was not intended to replace clinical breakpoint interpretation. RESULTS: CRKP accounted for 21.3% of K. pneumoniae bloodstream infections and remained associated with in-hospital mortality after adjustment for infection severity and source. By CLSI criteria, 83.1% of isolates were cefiderocol susceptible; the MIC50 and MIC90 were 4 and 8 mg/L, respectively, and 41.0% met the reduced-susceptibility definition. ST11 predominated, with KL47 and KL64 as the main capsular loci. Cefiderocol MICs were higher among KL47/KL64 and virulence-plasmid-associated isolates than among comparator backgrounds. In multivariable analysis, bla NDM-1, bla SHV-12, and the aerobactin locus remained associated with reduced susceptibility, although the findings require cautious interpretation because of limited sample size and possible effects of clonal background. No inactivating mutations were identified in cirA, fepA, or fiu. CONCLUSIONS: Borderline cefiderocol MIC elevation was present before local drug exposure and was more frequent in locally prevalent ST11-KL47/KL64 and virulence-plasmid-associated CRKP. These findings provide a bloodstream-specific pre-introduction baseline and support prospective surveillance of numerical MIC distributions and associated genomic backgrounds.

Cefiderocol