Dataset Information

Development of Persister-FACSeq: a method to massively parallelize quantification of persister physiology and its heterogeneity.

ABSTRACT: Bacterial persisters are thought to underlie the relapse of chronic infections. Knowledge of persister physiology would illuminate avenues for therapeutic intervention; however, such knowledge has remained elusive because persisters have yet to be segregated from other cell types to sufficient purity. This technical hurdle has stymied progress toward understanding persistence. Here we developed Persister-FACSeq, which is a method that uses fluorescence-activated cell sorting, antibiotic tolerance assays, and next generation sequencing to interrogate persister physiology and its heterogeneity. As a proof-of-concept, we used Persister-FACSeq on a library of reporters to study gene expression distributions in non-growing Escherichia coli, and found that persistence to ofloxacin is inversely correlated with the capacity of non-growing cells to synthesize protein. Since Persister-FACSeq can be applied to study persistence to any antibiotic in any environment for any bacteria that can harbor a fluorescent reporter, we anticipate that it will yield unprecedented knowledge of this detrimental phenotype.

SUBMITTER: Henry TC

PROVIDER: S-EPMC4855238 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of Persister-FACSeq: a method to massively parallelize quantification of persister physiology and its heterogeneity.

Henry Theresa C TC Brynildsen Mark P MP

Scientific reports 20160504

Bacterial persisters are thought to underlie the relapse of chronic infections. Knowledge of persister physiology would illuminate avenues for therapeutic intervention; however, such knowledge has remained elusive because persisters have yet to be segregated from other cell types to sufficient purity. This technical hurdle has stymied progress toward understanding persistence. Here we developed Persister-FACSeq, which is a method that uses fluorescence-activated cell sorting, antibiotic toleranc ...[more]

PMID: 27142337

Similar Datasets

Project description:BackgroundCartilage morphometry based on magnetic resonance images (MRIs) is an emerging outcome measure for clinical trials among patients with knee osteoarthritis (KOA). However, current methods for cartilage morphometry take many hours per knee and require extensive training on the use of the associated software. In this study we tested the feasibility, reliability, and construct validity of a novel osteoarthritis cartilage damage quantification method (Cartilage Damage Index [CDI]) that utilizes informative locations on knee MRIs.MethodsWe selected 102 knee MRIs from the Osteoarthritis Initiative that represented a range of KOA structural severity (Kellgren Lawrence [KL] Grade 0 - 4). We tested the intra- and inter-tester reliability of the CDI and compared the CDI scores against different measures of severity (radiographic joint space narrowing [JSN] grade, KL score, joint space width [JSW]) and static knee alignment, both cross-sectionally and longitudinally.ResultsDetermination of the CDI took on average14.4 minutes (s.d. 2.1) per knee pair (baseline and follow-up of one knee). Repeatability was good (intra- and inter-tester reliability: intraclass correlation coefficient >0.86). The mean CDI scores related to all four measures of osteoarthritis severity (JSN grade, KL score, JSW, and knee alignment; all p values < 0.05). Baseline JSN grade and knee alignment also predicted subsequent 24-month longitudinal change in the CDI (p trends <0.05). During 24 months, knees with worsening in JSN or KL grade (i.e. progressors) had greater change in CDI score.ConclusionsThe CDI is a novel knee cartilage quantification method that is rapid, reliable, and has construct validity for assessment of medial tibiofemoral osteoarthritis structural severity and its progression. It has the potential to addresses the barriers inherent to studies requiring assessment of cartilage damage on large numbers of knees, and as a biomarker for knee osteoarthritis progression.

Dataset Information

Development of Persister-FACSeq: a method to massively parallelize quantification of persister physiology and its heterogeneity.

Publications

Development of Persister-FACSeq: a method to massively parallelize quantification of persister physiology and its heterogeneity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets