In Vivo-Acquired Resistance to Daptomycin during Methicillin-Resistant Staphylococcus aureus Bacteremia.

Daptomycin (DAP) represents an interesting alternative to treat methicillin-resistant Staphylococcus aureus (MRSA) infections. Different mechanisms of DAP resistance have been described; however, in vivo-acquired resistance is uncharacterized. This study described the phenotypic and genotypic evolution of MRSA strains that became resistant to DAP in two unrelated patients with bacteremia under DAP treatment, in two hospitals in the South of France. DAP MICs were determined using broth microdilution method on the pairs of isogenic (DAP-S/DAP-R) S. aureus isolated from bloodstream cultures. Whole genome sequencing was carried out using Illumina MiSeq Sequencing system. The two cases revealed DAP-R acquisition by MRSA strains within three weeks in patients treated by DAP. The isolates belonged to the widespread ST5 (patient A) and ST8 (patient B) lineages and were of spa-type t777 and t622, respectively. SNP analysis comparing each DAP-S/DAP-R pair confirmed that the isolates were isogenic. The causative mutations were identified in MprF (Multiple peptide resistance Factor) protein: L826F (Patient A) and S295L (Patient B), and in Cls protein: R228H (Patient B). These proteins encoded both proteins of the lipid biosynthetic enzymes. The resistance to DAP is particularly poorly described whereas DAP is highly prescribed to treat MRSA. Our study highlights the non-systematic cross-resistance between DAP and glycopeptides and the importance of monitoring DAP MIC in persistent MRSA bacteremia.

Hemolysis interference on clinical chemistry tests analyzed on DxC 700 AU (Beckman Coulter®) and kaliemia rendering algorithm / Interférence de l'hémolyse sur les examens de biochimie clinique analysés sur DxC 700 AU (Beckman Coulter®) et algorithme de rendu de la kaliémie

The influence of hemolysis was evaluated for 26 clinical chemistry parameters on DxC 700AU (Beckman Coulter®). Ten sample pools were prepared and separated into six aliquots. These aliquots were overloaded with hemolysis in increasing amounts to reach levels equivalent to the maximum hemolysis thresholds H1 (+), H2 (++), H3 (+++) and H4 (++++). Each aliquot is compared to its reference aliquot (not hemolyzed) and a ratio is calculated for each parameter. We proposed that there was a significant difference if, for a given analyte and threshold, more than 20% of the ratios are above the total acceptable limit variability. A significant difference was found for TGP, TGO, cholesterol, creatine kinase (CPK), lactate deshydrogenase (LDH), phosphorus and potassium at H1 (+), chlorine, iron, γ-glutamyltransferase (GGT), and magnesium at H2 (++), amylase and alkaline phosphatase (PAL) at H3 (++++), and prealbumin at H4 (++++). No interference was found until H4 included for uric acid, calcium, creatinine, lipase, glucose, HDL-cholesterol, triglycerides, urea, sodium and immunoglobulins A, G and M. The overestimation of kalemia was calculated as a function of hemolysis, ranging from 0.28 mM +/­0.047 (upper H1 threshold) to 1.37 mM +/­0.126 (upper H4 threshold). Its estimation makes it possible to propose a result rendering algorithm of kalemia according to the hemolysis index. Evaluation of the automates hemolysis indexes is highly recommended for each laboratory. It can allow for some critical parameters the establishment of a decision tree facilitating the result rendering, after clinicobiological consultation.

L'influence de l'hémolyse a été évaluée pour 26 paramètres biochimiques sur l'analyseur DxC 700 AU (Beckman Coulter®). Dix pools d'échantillons ont été préparés et séparés en six aliquots surchargés en hémolysat selon une quantité croissante d'hémoglobine pour atteindre des niveaux équivalents aux seuils maximums d'hémolyse de l'automate H1(+), H2(++), H3(+++) et H4 (++++). Chaque aliquot est comparé à son aliquot de référence (sans hémolysat) et un ratio est calculé pour chaque paramètre. Nous proposons une différence significative si, pour un analyte et un seuil donné, plus de 20 % des ratios sont supérieurs à la variabilité limite totale acceptable (VLTA). Une différence significative est retrouvée pour ALAT, ASAT, cholestérol, créatine kinase (CPK), lactate deshydrogenase (LDH), phosphore et potassium dès H1, chlore, fer, γ--glutamyltransferase (GGT), et magnésium pour H2, amylase et phosphatase alcaline (PAL) pour H3, et préalbumine pour H4. Aucune interférence n'a été retrouvée jusqu'à H4 inclus pour acide urique, calcium, créatinine, lipase, glucose, HDL-cholestérol, triglycérides, urée, sodium et immunoglobulines A, G et M. La surestimation de la kaliémie a été calculée en fonction de l'hémolyse : elle varie de 0,28 mM ± 0,047 (seuil supérieur de H1) à 1,37 mM ± 0,126 (seuil supérieur de H4). Son estimation permet proposer un algorithme de rendu de résultat de la kaliémie selon l'index d'hémolyse. L'évaluation des index d'hémolyses de l'automate est, pour chaque laboratoire, fortement recommandée. Elle peut permettre, pour certains paramètres critiques, la mise en place d'un arbre décisionnel facilitant le rendu de résultat, après concertation clinicobiologique.

Escherichia coli Isolated from Diabetic Foot Osteomyelitis: Clonal Diversity, Resistance Profile, Virulence Potential, and Genome Adaptation.

This study assessed the clonal diversity, the resistance profile and the virulence potential of Escherichia coli strains isolated from diabetic foot infection (DFI) and diabetic foot osteomyelitis (DFOM). A retrospective single-centre study was conducted on patients diagnosed with E. coli isolated from deep DFI and DFOM at Clinique du Pied Diabétique Gard-Occitanie (France) over a two-year period. Phylogenetic backgrounds, virulence factors (VFs) and antibiotic resistance profiles were determined. Whole-genome analysis of E. coli strains isolated from same patients at different periods were performed. From the two-years study period, 35 E. coli strains isolated from 33 patients were analysed; 73% were isolated from DFOM. The majority of the strains belonged to the virulent B2 and D phylogenetic groups (82%). These isolates exhibited a significant higher average of VFs number than strains belonging to other groups (p < 0.001). papG2 gene was significantly more detected in strains belonging to B2 phylogroup isolated from DFI compared to DFOM (p = 0.003). The most prevalent antibiotic resistance pattern was observed for ampicillin (82%), cotrimoxazole (45%), and ciprofloxacin (33%). The genome analysis of strains isolated at two periods in DFOM showed a decrease of the genome size, and this decrease was more important for the strain isolated at nine months (vs. four months). A shared mutation on the putative acyl-CoA dehydrogenase-encoding gene aidB was observed on both strains. E. coli isolates from DFOM were highly genetically diverse with different pathogenicity traits. Their adaptation in the bone structure could require genome reduction and some important modifications in the balance virulence/resistance of the bacteria.

Effectiveness and Acceptance of Multimodal Antibiotic Stewardship Program: Considering Progressive Implementation and Complementary Strategies.

Multiple modes of interventions are available when implementing an antibiotic stewardship program (ASP), however, their complementarity has not yet been assessed. In a 938-bed hospital, we sequentially implemented four combined modes of interventions over one year, centralized by one infectious diseases specialist (IDS): (1) on-request infectious diseases specialist consulting service (IDSCS), (2) participation in intensive care unit meetings, (3) IDS intervention triggered by microbiological laboratory meetings, and (4) IDS intervention triggered by pharmacist alert. We assessed the complementarity of the different cumulative actions through quantitative and qualitative analysis of all interventions traced in the electronic medical record. We observed a quantitative and qualitative complementarity between interventions directly correlating to a decrease in antibiotic use. Quantitatively, the number of interventions has doubled after implementation of IDS intervention triggered by pharmacist alert. Qualitatively, these kinds of interventions led mainly to de-escalation or stopping of antibiotic therapy (63%) as opposed to on-request IDSCS (32%). An overall decrease of 14.6% in antibiotic use was observed (p = 0.03). Progressive implementation of the different interventions showed a concrete complementarity of these actions. Combined actions in ASPs could lead to a significant decrease in antibiotic use, especially regarding critical antibiotic prescriptions, while being well accepted by prescribers.