Bacterial Identification and Susceptibility Testing

This paper develops and validates an FTIR spectroscopy classifier for Salmonella serogroup differentiation, achieving >99% inclusivity for key serogroups.

GenomicGapID uses conserved genomic site spacing to create universal primers for broad microbial identification, achieving high coverage with few primer sets.

The paper evaluates metagenomic workflows for pathogen detection using NIST RM 8376 in CSF and stool samples, finding workflow-dependent strain discrimination and sample-agnostic detection responses.

The paper introduces Maldi Transformer, a pre-trained model for MALDI-TOF MS data that improves prediction tasks through self-supervised learning.

This paper develops a dual-branch neural network to predict antimicrobial resistance profiles from MALDI-TOF MS data, improving treatment efficiency and enabling fine-tuning across clinical labs.

This study compares 16S rRNA gene sequencing with conventional PCR for bacterial identification and disease diagnosis, finding that sequencing is more sensitive and effective in detecting pathogens and distinguishing healthy from diseased samples.

This paper introduces a universal bacterial identification system using ITS-targeting primers that outperforms existing methods in speed, cost, and taxonomic breadth.

The paper develops a triplex real-time PCR assay (ZKIR-T) to detect all Klebsiella pneumoniae species complex members and specifically identify K. pneumoniae sensu stricto.

This paper develops machine learning models using MALDI-TOF MS data to predict antimicrobial resistance in Staphylococcus epidermidis, achieving high AUROC and AUPRC scores.

This study demonstrates rapid detection of pathogens and antimicrobial resistance genes in urine using Nanopore sequencing within five hours.

This paper introduces a lipidomics-based method, FLAT, to rapidly identify negative urine cultures in UTI suspects with high accuracy, improving diagnostic efficiency.

This study evaluates three blood culture media for antimicrobial neutralization, finding BACT/ALERT media outperformed others in recovery rates, while Thermo media had the lowest performance.

This paper develops a method combining LC-SRM and machine learning to rapidly identify and quantify bacterial pathogens in UTIs with high accuracy.

The paper evaluates phenotypic and genotypic methods for identifying and characterizing bacterial isolates from catheter-associated urinary tract infections, finding no consensus across methods and highlighting the importance of whole genome sequencing for accurate identification.

The paper introduces a high-throughput antibiotic susceptibility testing method using a Multipad Agarose Plate that reduces turnaround time by eightfold.

GAMBIT uses k-mer based strategies and a curated database to identify bacteria from whole genome sequencing with confidence thresholds to reduce false identifications.

This study evaluates a pilot proficiency testing program for bacterial whole genome sequencing in clinical and public health labs, showing labs can generate and analyze high-quality data using diverse bioinformatics tools.

The paper introduces a web-based tool for identifying Klebsiella isolates at species complex and phylogroup levels using MALDI-TOF mass spectrometry data.

This study annotates ribosomal protein mass peaks in MALDI-TOF mass spectra of bacterial species and finds they hold phylogenetic significance, though structural conservation is not observed.

This paper presents an RNA signature-based platform for rapid antimicrobial susceptibility testing of Neisseria gonorrhoeae using RNA markers validated across multiple isolates.

The paper validates a clinical metagenomic sequencing assay for detecting pathogens in cerebrospinal fluid, showing 73% sensitivity and 99% specificity compared to clinical tests.

This paper develops a metagenomic sequencing approach to diagnose lower respiratory tract infections by integrating pathogen detection, microbiome analysis, and host transcriptome data.

The paper develops a portable system using nanopore sequencer and laptop computers for rapid on-site bacterial composition analysis, showing comparable or better results than conventional methods.

This study uses metagenomic sequencing to detect respiratory pathogens in hematopoietic transplant patients, finding it more sensitive than conventional methods and identifying new pathogens.