| Title |
Added Value of Next-Generation Sequencing for Multilocus Sequence Typing Analysis of aPneumocystis jiroveciiPneumonia Outbreak1
|
|---|---|
| Published in |
Emerging Infectious Diseases, August 2017
|
| DOI | 10.3201/eid2308.161295 |
| Pubmed ID | |
| Authors |
Elena Charpentier, Cécile Garnaud, Claire Wintenberger, Sébastien Bailly, Jean-Benjamin Murat, John Rendu, Patricia Pavese, Thibault Drouet, Caroline Augier, Paolo Malvezzi, Anne Thiébaut-Bertrand, Marie-Reine Mallaret, Olivier Epaulard, Muriel Cornet, Sylvie Larrat, Danièle Maubon |
| Abstract |
Pneumocystis jirovecii is a major threat for immunocompromised patients, and clusters of pneumocystis pneumonia (PCP) have been increasingly described in transplant units during the past decade. Exploring an outbreak transmission network requires complementary spatiotemporal and strain-typing approaches. We analyzed a PCP outbreak and demonstrated the added value of next-generation sequencing (NGS) for the multilocus sequence typing (MLST) study of P. jirovecii strains. Thirty-two PCP patients were included. Among the 12 solid organ transplant patients, 5 shared a major and unique genotype that was also found as a minor strain in a sixth patient. A transmission map analysis strengthened the suspicion of nosocomial acquisition of this strain for the 6 patients. NGS-MLST enables accurate determination of subpopulation, which allowed excluding other patients from the transmission network. NGS-MLST genotyping approach was essential to deciphering this outbreak. This innovative approach brings new insights for future epidemiologic studies on this uncultivable opportunistic fungus. |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 38% |
| Guatemala | 1 | 6% |
| United Kingdom | 1 | 6% |
| Netherlands | 1 | 6% |
| Unknown | 7 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 56% |
| Scientists | 6 | 38% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 17% |
| Student > Ph. D. Student | 4 | 14% |
| Researcher | 4 | 14% |
| Student > Doctoral Student | 2 | 7% |
| Student > Postgraduate | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 9 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 24% |
| Agricultural and Biological Sciences | 4 | 14% |
| Biochemistry, Genetics and Molecular Biology | 4 | 14% |
| Immunology and Microbiology | 3 | 10% |
| Economics, Econometrics and Finance | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 10 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 July 2017.
All research outputs
#3,088,598
of 24,829,155 outputs
Outputs from Emerging Infectious Diseases
#3,046
of 9,587 outputs
Outputs of similar age
#54,638
of 322,373 outputs
Outputs of similar age from Emerging Infectious Diseases
#53
of 117 outputs
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