Current Issue: 2019  Archive: 2018  Archive: 2017 

Genotyping Pneumocystis jirovecii: Impacting Our Understanding of Interhuman Transmission

Maud Gits-Muselli 1, 2, 3 * , Stéphane Bretagne 1, 2, 3 , Alexandre Alanio 1, 2, 3 

  1. Institute Pasteur, Molecular Mycology Unit, National Reference Center for Invasive Mycoses and Antifungals, Paris, France
  2. Parasitology-Mycology Laboratory, Saint-Louis Hospital, Assistance Publique-Hôpitaux de Paris
  3. Paris-Diderot, Sorbonne Paris Cité University, Paris, France

*   Correspondence: Maud Gits-Muselli 

Received: December 4, 2018 | Accepted: January 8, 2019 | Published: January 18, 2019

OBM Genetics 2019, Volume 3, Issue 1 doi: 10.21926/obm.genet.1901060

Academic Editors: Andrés Moya, Enrique J. Calderón and Luis Delaye

Special Issue: Pneumocystis: A Model of Adaptive Coevolution

Recommended citation: Gits-Muselli M, Bretagne S, Alanio A. Genotyping Pneumocystis jirovecii: Impacting Our Understanding of Interhuman Transmission. OBM Genetics 2019;3(1):20; doi:10.21926/obm.genet.1901060.

© 2019 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.


Pneumocystis jirovecii is an atypical fungus transmitted via the airborne route between humans. This fungus is exclusively associated with humans and almost each individual has encountered it at least once before reaching the age of two. P. jirovecii can be cleared and spontaneously resolutive in immunocompetent, whereas it can be responsible for severe Pneumocystis pneumonia (PCP) in immunocompromised patients. In the next decades, the putative increase of the population of immunocompromised patients is likely to lead to the rise of PCP infections. The detection of low fungal loads has been improved with the advances of molecular technologies and polymerase chain reaction (PCR) assays. This improvement in detection raised several questions. Is PCP consecutive of a persistent colonizing strain multiplication or acquisition of a new one? What is the variety of strains in PCP and non-PCP patients? Are outbreaks due to a specific strain? Genotyping approaches could bring some answers. In this review, we reviewed the main typing methods developed for P. jirovecii characterization, with an emphasis on the typing of low fungal loads, a subject rarely underlined. Secondarily, we present the main results obtained and the importance of including patients with low fungal load in the analyses because of their possible role as reservoirs and their impact on P. jirovecii transmission. Finally, we consider systematic treatment of the patients with low fungal load not only to prevent full-blown PCP, but also to block the transmission chain.


Pneumocystis jirovecii; genotyping; methods; review

1. Introduction

Pneumocystis jirovecii is considered a commensal fungus of the pulmonary alveoli and is peculiar in the fungal world because of the direct interhuman transmission in its life cycle with no known environmental reservoir [1,2]. This atypical fungus is exclusively associated with humans and almost each individual has encountered it at least once before reaching the age of two [3,4,5,6]. Pneumocystis jirovecii can exhibit spontaneously resolutive symptoms in infants and is also responsible for severe pneumocystis pneumonia (PCP) in immunocompromised patients, such as HIV-positive patients, solid organ transplant patients, patients with hematological malignancies, or patients given high dose steroids or anti-TNF drugs [7,8,9,10]. The increase of the population of immunocompromised patients is likely to lead to the rise of PCP infections in the coming decades.

With the advances of molecular technologies and polymerase chain reaction (PCR) assays, the detection of low fungal loads has been improved compared with microscopy, leading to the concept of carriage when detection was not clinically associated with pulmonary symptoms [11].

Consequently, detection of P. jirovecii DNA in non-PCP patients has raised several physiopathological questions. For instance, is PCP due to reactivation of a colonizing strain or acquisition of a new one? Are the strains in PCP and non-PCP patients similar? Are outbreaks due to a specific strain? Most of these questions can be addressed using genotyping, which must be performed directly on clinical specimens because of the absence of reliable culture methods [12].

P. jirovecii genotyping strategies have been debated in several reviews [13,14]. Recently, Alanio et al. also proposed a review on fungi genotyping strategies with a focus on P. jirovecii [15]. Other reviews were published earlier on this question [16,17,18].

To continue on this topic, we firstly consider the main typing methods developed for P. jirovecii characterization and their pros and cons, with an emphasis on the typing of low fungal loads, a subject rarely underlined. Secondarily, we present the main results obtained and the importance of including patients with low fungal load in the analyses because of their possible role as reservoirs and their impact on P. jirovecii transmission. Finally, we open the debate on systematic treatment of patients with low fungal load not only to prevent full-blown PCP, but also to block the transmission chain.

2. Genotyping Methods

There is no ideal method for genotyping fungi, the one that shows the most potential would be technically accessible and easy to perform, achievable at a reasonable cost, and have good reproducibility [15]. An additional feature would be performance, defined as the ability to target a marker that remains stable during the study period and is testable in every sample [19,20]. The selected methods should also be capable of detecting mixtures, and in particular, have the ability to detect minority alleles. Detection of mixtures is an important aspect in the study of P. jirovecii transmission and epidemiology, considering that up to 92% of patients’ respiratory samples present coinfections [17,21,22,23,24,25].

Finally, the method should be discriminant. The discriminatory power of a method can be determined using Simpson’s Diversity Index, which uses probability to assign a value of diversity to two unrelated strains sampled randomly from the population of a given species [26].

Several genotyping methods have been used to study epidemiology, strain variation, and resolve transmission events of Pneumocystis in humans. A brief chronological summary of the usual methods is given in Table 1.

2.1 Single-Strand Conformation Polymorphism (SSCP)

SSCP detects single-strand conformation polymorphisms created by a single nucleotide polymorphism [27]. This nucleotide polymorphism leads to a change of mobility of single-stranded DNA under non-denaturing electrophoretic conditions. The method is easy to perform, presents a low cost, and allows identification of nucleotide variation in amplicons ranging from 100 to 500bp. Moreover, this method can detect mixtures with a detection threshold around 10% [28,29].

Several loci have been targeted for P. jirovecii typing with this method: internal transcribed spacer 1 (ITS1) region, the 26 rRNA gene (26S), the mitochondrial 26S rRNA gene (mt26S), a partial portion of the β-tubulin gene as proposed by Hauser in 1997, and also the dihydropteroate gene (dhps), which was added to this list by Ma and Kovacs in 2001 [28,29,30,31]. SSCP results are limited by the quality of the migration of the DNA fragments and has been progressively abandoned.

2.2 Restriction Fragment Length Polymorphism Analysis (RFLP)

RFLP typing has been widely used for many pathogens. RFLP includes an amplification of the selected loci followed by DNA digestion using restriction enzymes, which excludes loci lacking of restriction sites. The digested and amplified fragments are then analyzed by gel electrophoresis. This method is limited by the need for a high amount of fungal DNA in the patients’ sample, as a low amount could lead to a poor signal [32]. Sensitivity could be increased with the use of hybridization with a probe specific for the amplified locus, which requires the use of radioactivity. The band patterns obtained allow the determination of sequence similarities or differences. This method is fast, cheap, and easy to perform. Nonetheless, result analysis is challenging; slight differences in band patterns could be missed. This difficulty in assigning a definite size limits data exchange between laboratories.

Several targets have been used for P. jirovecii typing with this method. RFLP analysis targeting the major surface glycoprotein family A1 gene (msg-RFLP) was proposed in 2009 and successfully used to investigate outbreaks in two centers receiving renal transplant patients [32,33]. The msg-RFLP assay targets a 1300 bp fragment of the A1 msg gene subfamily, which is described as highly polymorphic [14,34,35]. This method was also used in addition to a multilocus sequence typing (MLST) scheme of 3 loci to investigate an outbreak in a Danish transplant center [36].

The dhps gene of P. jirovecii has also been used for RFLP typing, but the polymorphism is limited to only two single nucleotide polymorphism (SNP) positions at nucleotides 165 and 171 [37,38,39,40]. As a consequence, this marker cannot be used alone for genotyping.

2.3 Direct DNA Sequencing

2.3.1 Single Locus

Sanger sequencing of selected loci is easily accessible for most medical facilities. Several loci have been tested which can be divided into genomic and mitochondrial markers.

Internal transcribed spacer ITS1 and ITS2 are very polymorphic genomic loci and have been used in numerous studies [16,18,41,42]. At least 60 unique genotypes have been deposited in GenBank. Of note, ITS1 and ITS2 frequently present poly (T) and poly (A) repetitions of variable lengths within the same strain. Such polymorphisms could hamper alignment of downstream sequences [31,42,43]. ITS markers are often included in MLST schemes and NGS studies as described hereafter.

Mitochondrial markers, such asthe mitochondrial small (mtSSU) and large subunit rRNA (mtLSU) genes, were used for direct DNA sequencing, phylogeny studies, and genotyping, with at least 25 unique mtSSU and 5 unique mtLSU genotypes reported in GenBank [13,44,45]. mtSSU or mtLSU genes appear less discriminant than ITS1 and ITS2 [18,46]. Nevertheless, complete mitochondrial genome analysis revealed a 1-kb noncoding region rich in polymorphic sites, including both tandem repeats and single nucleotide polymorphisms [47]. This 1-kb polymorphic region discriminated at least 20 unique P. jirovecii genotypes in 23 clinical samples [47].

Other genes have been used for genotyping studies: mitochondrial genes, such as genes encoding cytochrome b (cob); nuclear genes such as β-tubulin; thymidylate synthase (ts); dihydropteroate synthase (dhps); dihydrofolate reductase (dhfr); superoxide dismutase (sod); the multifunctional product of arom; kexin (kex1); and thioredoxin reductase 1 (trr1) [44,48,49,50,51,52,53,54,55,56,57,58,59].

Although Sanger sequencing is easily affordable, a single given locus is not sufficient to represent the polymorphism of P. jirovecii in a clinical sample. Therefore, several markers have to be associated in an MLST scheme (see below), which limits the throughput and increases the cost. Additionally, Sanger sequencing cannot detect minority alleles below a 20-30% threshold.

2.3.2 Allele-Specific PCR

In this method, described by Keely et al., an allele-specific PCR assay is designed for identifying genotype switching in patients presenting two PCP episodes [60]. The target is the mtrRNA large subunit (mtLSU) locus already known to be polymorphic at site 85. This allele-specific assay requires two steps: the first step is a pre-amplification of the targeted 346 base pair mtrRNA amplicon. The second step consists of parallel PCRs using a specific primer designed to amplify DNA with a C at site 85, or using a specific primer designed to amplify DNA with an A at site 85. Amplified DNA is then subjected to electrophoresis in agar gel and hybridized with a labelled probe for detection. This approach allowed the comparison of the mt85 profile (A or C) between PCP episodes. This allele-specific PCR provided arguments for the re-infection hypothesis versus reactivation of latent microorganisms. This method was used to investigate several episodes in a given individual but is not fully adapted to discriminate between genotypes to investigate outbreaks.

2.3.3 DNA Sequencing Using a Multilocus Sequence Typing

The multilocus sequence typing (MLST) method involves PCR amplification and DNA sequencing of a set of loci [61]. Thereafter, an allele is assigned to the sequence of each gene in a given sample and the combination of alleles defines the sequence type corresponding to the specific allelic profile [62]. Numerous markers have been evaluated in MLST schemes for P. jirovecii genotyping (ITS region,26S rDNA, mt26S, β-tubulin, sod, cytochrome b, mtLSU rRNA gene, as well as dhps and dhfr genes) and different combinations of genetic loci have been proposed [17,63,64,65,66,67,68]. A common nomenclature for the various alleles of these MLST markers has led to the creation of a specific web page ( to harmonize the results. Each of the different sets proposed had a high discriminatory power, but there were few comparative studies of the different MLST schemes and the choice and the number of the loci are not standardized. In 2013, Maitte et al. evaluated different combinations in regard to their discriminatory power on 33 epidemiologically unrelated patients. The discriminatory power of the different combinations ranged from 0.751 using one marker to 0.996 using eight markers, and the authors proposed an optimized MLST scheme restricted to three loci (ITS, mt26S, and cyb) which achieved a discriminatory power of 0.996 [63]. The MLST approach was used in outbreak investigations and confirmed the presence of identical genotypes recovered from different patients during outbreaks [69,70,71]. Nevertheless, MLST remains labor-intensive to achieve amplification and sequencing of multiple individual loci from individual respiratory samples. Esteves et al. skirted these disadvantages by using DNA pooling of samples before genotyping. In Esteves's study, DNA pooling enabled cost reduction by using fewer PCR reactions before sequencing [72].

2.4 Single-Base Extension Methods (SBE)

These methods are based on already known SNP detections at different loci [73]. In single-base extension methodologies (SBEs), the first step consists of the amplification of the selected loci (with multiplex PCR or not) containing the known SNPs. This step is followed by the SBE assay using specific primers designed to hybridize to the targeted DNA sequence just immediately upstream of the polymorphic site of interest. These specific primers can be paired with tags for further discrimination if multiplex analysis is needed. The specific primer hybridizes with the targeted complementary region and this hybridization allows the enzymatic extension by a single base in the presence of the four ddNTPs. Thus, the ddNTP complementary to the polymorphic base could be incorporated, the elongation stopped, and then be identified. The identification of this incorporated base can be determined by fluorescence labelling, isotope labelling, or size determination using electrophoresis.

Esteves et al. used this method on P. jirovecii in 2011 on three genetic targets (dhfr, mtLSU rRNA, and sod) with four SNP positions (dhfr312, mt85, sod110, and sod215) [74]. The concordance for genotyping was 94% using capillary electrophoresis when compared to direct sequencing. Esteves et al. then successfully used this method with high throughput abilities [75]. In Esteves's multicenter study, SBE enabled the clustering of genotypes according to their geographical origin (samples from Portugal, USA, Spain, Cuba, and Mozambique) and a specific haplotype (DHFR312T/SOD110C/SOD215T) appeared as associated with severe AIDS-related PCP.

Alanio et al. also used the SBE approach on the mt85 locus (analyzing three alleles) and found a correlation between allele type and the place of hospitalization [76] . This approach also enables the detection of minor variants in mixed samples. This method is suited for studying minority variants but is limited as a genotyping method to investigate outbreaks, considering the use of a restrictive number of SNP positions. Moreover, this method remains costly when compared to Sanger sequencing.

2.5 Short Tandem Repeat (STR)

Short tandem DNA repeats (or microsatellites) are found in numerous loci in eukaryotes and one of their features is a high mutation rate [77]. Due to slipped strand mispairing during the DNA replication process, STR loci have been found to mutate at 10 to 100,000 times more frequently than non-repetitive elements in eukaryotic genomes [78,79]. The method to determine the size of the repetitive element consists of the amplification of the target locus followed by a capillary electrophoresis. The combination of several STRs have already been used for several pathogens [80,81,82,83].

The first STR locus used for P. jirovecii is located in the intron of the upstream conserved sequence (UCS) of the msg gene. This locus presents a 10-bp repetitive motif with three sequence types observed, and a variety for each sequence type determined according to the number of repeats of the motif [24,58,84,85]. In 2012, the availability of P. jirovecii genome published by Cisse et al. allowed the identification of numerous loci as possible STRs [86]. The first study using STR analysis published by Parobek and colleagues in 2014 is based on eight STR markers and was validated using 91 P. jirovecii-positive respiratory specimens collected in patients from Uganda, the United States, and Spain [87]. The discriminatory power reached in this study was 0.999. Another STR analysis scheme (with one locus in common with Parobek’s study) was proposed in 2015 and was based on six STR markers [22]. In studying 106 respiratory specimens (corresponding to 91 patients), the discriminatory power was 0.992 after the exclusion of putative epidemiologically related samples. This method was subsequently used to investigate P. jirovecii strains’ population structure via a collaboration between European teams [23].

Regarding the ability to determine mixtures of P. jirovecii genotypes in samples, STR typing studies reported 70% (Parobek) and 68% (Gits-Muselli) of genotype mixtures, which was confirmed with a European study that analyzed 249 samples (68% of mixtures) [22,23,87]. The maximal ratio of mixture detection using simulated mixed samples was 1/50 [22].

Although this method is easy to use, fast, cheap, and without need of sequencing, STR typing is not standardized and selection of the best STR markers remains to be established. As a consequence, no database for reporting and inter-laboratory comparison is currently available.

2.6 Next-Generation Sequencing (NGS)

NGS encompasses a lot of different applications from genome assembly to amplicon analyses. These applications do not require the same equipment and the same procedures.

P. jirovecii whole genome assembly, Cisse et al. performed whole genome sequencing on a single bronchoalveolar lavage (BAL) sample. Before sequencing assays, the BAL sample was enriched in P. jirovecii by immunoprecipitation. Nucleic acids were then extracted and sequenced using high throughput sequencing methodologies. Roche's 454 and Illumina's paired-end approaches were used to construct the libraries. Indeed, the lack of culture systems for P. jirovecii in a global approach to sequencing resulted in a huge quantity of undesirable DNA from humans and other microorganisms present in the BAL fluid; a dedicated software was used to eliminate human sequences [86].The first assembly was followed by a second one in 2015, and this allowed genome comparison of two different strains [34]. A recent study by Cissé et al. compared the whole genome sequence of 33 P. jirovecii strains to determine genomic variation and population structure [88]. This study found that the natural population maintains a high level of genetic variation despite low levels of recombination.

Nonetheless, comparison of several clinical strains using whole genome sequencing (WGS) for genotyping is currently limited by the cost and the complexity of some analyses requiring bioinformaticians.

However, amplicon analysis using NGS can answer some questions on genotyping and does not require specific training in bioinformatics. Alanio et al. used the Roche GS Junior System to evaluate the diversity of P. jirovecii strains associated with acute infection [21]. Two nuclear (DHFR and ITS2) loci and one mitochondrial (mtLSU) locus were targeted using ultra-deep pyrosequencing. NGS revealed that 92% of patients harbored mixtures of genotypes with variable proportions during the course of infection. This study also highlighted the possibility of heteroplasmy, with the observation of more variants for the mtLSU locus than for nuclear loci.

Recently, few studies have been published using NGS amplicon analysis for P. jirovecii outbreak investigations. In 2016, Urabe et al. [89] published an outbreak investigation study using a MLST scheme on four loci: B-tubulin, 26S, SOD, and CYB. The MLST interpretation was limited by the overlapping of certain bases. In this study, MLST was followed by MiSeq NGS that allowed the identification of the ratio of these overlapping bases observed in the samples by Sanger sequencing. The NGS showed almost identical ratios of the different types of bases in the tested samples. The limit of the MLST approach with detection of overlapping bases at SNP positions was avoided by the addition of NGS.

The same approach was used by Charpentier et al. [90] to investigate an outbreak in Grenoble University Hospital. Three MLST loci (mtLSU, SOD, and CYB) were used and the GS Junior System was used to sequence modified amplicons of 700-800 bp fragments. The limit of variant detection was 1:100. This study confirmed the previous result of Alanio et al. on mitochondrial marker diversity, with a higher number of haplotypes compared to the nuclear markers.

NGS methodologies are useful to study diversity and mitigate the limits of other genotyping methods, however, they are costly and somewhat time-consuming.

3. Main Results of P. jirovecii Genotypes

3.1 Mixtures of P. jirovecii Genotypes

To date, all typing methods have reported the presence of mixtures of two or more genotypes in a single pulmonary sample but with different frequencies, as mixture detection depends on the depth of the analysis. Thus, the range of mixture detection varies according to the method used, from 30% using Sanger DNA sequencing to 70% using SSCPs [24,28,32,45,68,76,91,92] and STRs [23,87] to 90% using pyrosequencing [21]. Recently, implementation of STR analysis methods and next-generation sequencing (NGS) has allowed easy detection of low amounts of coinfecting genotypes, with ratios of about 1:50 and 1:1,000, respectively [22,90]. Mixtures are generally encountered with P. jirovecii infections, and it does not seem to depend on the underlying disease since mixture detection was as high in AIDS patients as in solid organ transplant recipients [22,23].

Mixture detection complicates epidemiological investigations when needing to attribute a given genotype to a given patient when mixtures are detected. Moreover, mixture detection not only depends on the method used but also on the fungal load. If the fungal load is too low, amplification of some single copy loci can fail, possibly hampering the analysis of genotyping and the detection of mixtures. This could introduce biases if low fungal loads are associated with specific genotypes [76].

3.2 Resistance to Co-Trimoxazole

A specific clinical issue has emerged with the use of trimethoprim-sulfamethoxazole (co-trimoxazole) prophylaxis of patients with PCP and AIDS. Although dhps mutations have been reported in PCP treatment failure (suggesting selection by drug pressure), the same mutations have also been detected in PCP patients not receiving co-trimoxazole, and no difference was evidenced regarding mortality in patients harboring wild type or mutant strains [38,93]. Therefore, rather than selection pressure by co-trimoxazole prophylaxis, the presence of dhps mutations could be explained by incidental interhuman transmission and may serve as an epidemiological marker rather than a resistance marker [94,95]. For instance, in a French study evaluating dhps mutation frequency from different parts of the country, dhps mutants were reported only in Paris, where exchanges between people could have been facilitated by population density rather than a pressure by co-trimoxazole prophylaxis [40].

3.3 Outbreak Investigations

Outbreak investigations have been the main application of genotyping. All the methods reported above have been used. To date, there is no definitive demonstration of superiority of one method over another. To demonstrate that two genotypes are different, there is no need for a very discriminant method after the difference is observed. In contrast, to demonstrate that two genotypes are identical, the most discriminant method should be used. The increased access of NGS technologies will probably change the way we perform outbreak investigations in the future, acknowledging that the presence of mixtures of P. jirovecii make the analysis of generated sequences difficult.

Outbreaks or clustered cases of PCPs have been reported in different settings, including kidney transplant units, liver transplant units, pediatric oncology wards, hematology wards, and wards of other medical specialties [66,96,97,98,99]. These outbreaks confirmed the currently accepted hypothesis of airborne transmission between humans, with the ascus (previously called the cyst) as the most probable infecting agent [100,101].

The search for index cases was also part of the outbreak investigations. The genotypes from PCP patients and carriers did not differ, and carriers can harbor P. jirovecii for long periods [102]. Thus, all carriers, and probably all individuals, can potentially act as a reservoir and transmit the fungus to immunocompromised hosts, as extrapolated from transmission experiments in mice [103,104]. Thus, transmission could occur between healthy individuals (such as healthcare workers) and immunocompromised patients as already suggested [105,106,107]. Indeed, health care workers would be able to transmit P. jirovecii for quite a long time, since P. jirovecii was detected in specific healthy individuals for up to 10 weeks [107].

Immunocompromised patients without full-blown PCP can also serve as a transmitter. The recent study of Robin et al. In stem cell transplant patients using STRs evidenced transmission in daycare centers between patients without clinical signs of PCP that harbored low fungal loads in their respiratory samples [98]. This underlies the need of prophylaxis in different clinical situations of immunosuppression using co-trimoxazole [9,108]. Prophylaxis could not only prevent PCP in a patient at risk, but would also decrease the fungal load of colonized patients and therefore potential transmission to other immunocompromised patients who may share or visit the specialized wards. Prophylaxis would then have a broader protective ability than individual protection.

For outbreak investigations, genotyping alone cannot ascertain transmission and contact between patients must also be included in the analysis [15]. The timing between exposure and disease (incubation time) has not been clearly defined. Therefore, when PCP occurs in a hospital setting, it remains unanswered when a possible transmission occurred. Recently, transmission of a specific genotype between renal transplant recipients, hematology patients, and cancer patients of a specific hospital have been studied over a period of 4 years. The median time between suspected exposure and PCP was 197 days (interquartile range: 57-342.5), suggesting that the incubation time of PCP is variable and can be as long as 3 months, even in the hospital and in immunocompromised individuals [22].

3.4 Choice of Genotyping Markers

When considering the choice of markers to use for genotyping, the current debate is not in favor of using mitochondrial markers, since mitochondrial and nuclear genomes drift at different speeds [109]. Notably, Alanio et al. described that mixed mitochondrial genotypes were associated with the highest fungal loads [76]. This either suggests coinfections with several genotypes or the accumulation of mutations due to a high replication rate of the microorganism rather than specific geographical localizations. The observation suggesting heteroplasmy with mixtures of mitochondrial DNA and unique nuclear markers also supports a precocious use of mitochondrial markers for studying population genetics [21,110].

3.5 Latent Versus Recently Acquired Infections

With the constant airborne circulation of P. jirovecii, PCP could not only be due to reactivation of latent disease acquired in childhood as in Cryptococci, but could also be the consequence of recent exposure [3,111,112]. This latter hypothesis comes from the observation of mixtures (see above), which can reach from 70% to more than 90% of cases, depending on the detection method used [4,21,113]. These mixtures can come from mutations of the initial organism contracted in infancy, resulting from microevolution in a single host. On the other hand, these mixtures can originate from continuous inhalation of new genotypes of varying frequency, given that different genotypes can be inhaled simultaneously or sequentially. Detection and genotyping of P. jirovecii DNA in the air surrounding individuals with or without active PCP reveals the connection between the human source and the acquisition of a specific genotype from other individuals in a specific period of time and at a given location [18,64].

The description of outbreaks or clustered cases in different settings (see above) favors the hypothesis of constant inhalation of different genotypes. Indeed, the sharing of a given genotype suggests recent acquisition and proliferation of a particular P. jirovecii genotype responsible for the outbreak in potentially P. jirovecii-naïve patients. Another argument for recent acquisition is that genotypes found during PCP were more closely related to the place of PCP diagnosis rather than to the place of birth, reinforcing the hypothesis of newly acquired P. jirovecii infection in hospital settings [114,115].

However, both mechanisms could occur simultaneously or sequentially: reactivation of P. jirovecii from prior exposure and multiplication from recent P. jirovecii exposure. The organism acquired in the past could be controlled by the immune system, resulting in equilibrium between host response and multiplication of the microorganisms, which becomes undetectable using the current PCR methods since around 70-80% of the BAL fluids tested in microbiology laboratories are negative. When a new microorganism with different surface proteins is inhaled, this new microorganism can cause a new illness as long as the immune response has not reached a new equilibrium as already suggested [13,116,117].

The polymorphism of the surface proteins prompts us to understand whether some microorganisms, possibly linked to different genotypes, are more prone to induce infection or more prone to proliferate compared to others, or if some genotypes are more specific to a given host’s background. Our multicenter study on European genotyping suggested that some specific genotypes could be linked to the patient’s background. A specific genotype (named Gt123) was observed in kidney transplant recipients and could be associated with a particular virulence for these patients presenting the same type of immunosuppression [23].

3.6 “Colonization” or “Carriage” of P. jirovecii

The concept of “colonization” or “carriage” of P. jirovecii was introduced as soon as P.jirovecii DNA was detected using PCR in patients without any symptoms, although at risk for PCP [118]. This concept has been extensively reviewed [11]. HIV infection, malignancies, solid organ transplantation, or immunosuppression secondary to immunosuppressive drugs including steroids, increases the prevalence of P. jirovecii detection in asymptomatic patients. However, the prevalence of this colonization is very variable from one study to another; this may result from the PCR method used or also from the patient cohorts studied with different levels of immuno-depression [11]. P. jirovecii DNA has also been detected in non-immunosuppressed patients, such as those with chronic lung diseases, cigarette smokers, or in pregnant women [11]. Until recently, most have assumed that the concept of "colonization" owns a specific status which have been brought in opposition with PCP [11] In contrast, colonized patients (either immunocompetent or immunocompromised individuals) can be considered as recently exposed patients with P. jirovecii, and thus serve as the reservoir of the organism, at least transiently, as discussed above. Consequently, we proposed that “colonization” could be considered as a situation where people have recently encountered P. jirovecii. In those individuals, only the immune status will predict if infection with symptoms will occur. Thus, what is called “colonization” or “asymptomatic carriage” could be the starting point for PCP in immunocompromised patients and therefore should not be neglected, as a possibility in addition to recent acquisition or reactivation of previous infection. For instance, Mori et al. demonstrated that patients receiving immunosuppressive therapy for rheumatoid arthritis tested positive for P. jirovecii DNA without respiratory symptoms and then developed PCP in the next 2 to 4 weeks [119]. Upon P. jirovecii exposure or reactivation in immunocompromised hosts, the fungal load (which is initially not detectable) increases until it plateaus at the stage of PCP [120]. The rapidity of this increase varies according to the immune status and the degree of immunosuppression.

3.7 Geographical Distribution

The European STR study of P. jirovecii on 249 samples described wide genotype diversity across Europe, and highlighted local clusters of patients infected with a given genotype. The previous study by Parobek et al. using STRs also described a wide variety of genotypes and suggested that the genetic differences between samples from Uganda, the United States, and Spain is limited when evaluating genetic distance using Rst and Fst, two classical factors to measure population demographic history with microsatellite markers [121]. Fst is statistical measure used to examine the overall genetic divergence in allele repartition among subpopulations. Rst is associated with genetic distance of microsatellites. In the Parobek et al. study, RST and FST suggested that Ugandan samples were significantly divergent from the San Francisco and Spain populations, but the study is limited by reduced sampling. Nonetheless, genetic differentiation was limited when considering all three populations. The recent study of Cissé et al. using whole genome sequencing found no evidence of population structuring by geography [88].

4. Conclusion and Perspective

The current observations reinforce the hypothesis that immunocompromised infants or adults could be a reservoir of P. jirovecii as well as immunocompetent individuals, at least transiently. Thus, immunocompetent individuals could be a potential source of constant circulation of the fungal organism in the population with the risk of transmission to potentially immunocompromised hosts. There is a need to study the different surface proteins and how the fungus can switch from one to another to explain the maintenance of transmission, despite the response of the immune system.

To further investigate transmission in humans, genotyping tools should be able to characterize low to very low amounts of P. jirovecii DNA in order to reveal whether these low loads correspond to quiescent forms or present the same polymorphism as the general population. New diagnostic tools allowing a more precise description of the metabolic state of P. jirovecii in a given sample or patient would be also needed. Consequently, anti-Pneumocystis treatment, such as co-trimoxazole, could be postponed to avoid side effects if P. jirovecii is in a latent state.

Table 1 Summary Methods Advantages and Pitfalls.


No specific acknowledgments for this review.

Author Contributions

MGM, SB and AA contributed equally to this work.


The authors have declared that no competing interests exist.


  1. Alanio A, Bretagne S. Pneumocystis jirovecii detection in asymptomatic patients: what does its natural history tell us? [Internet]. London: F1000Res; 2017 [cited 2018 Sep 27]. Available from:
  2. Gigliotti F, Wright TW. Pneumocystis: where does it live? PLoS Pathog. 2012; 8: e1003025. [CrossRef]
  3. Vargas SL, Hughes WT, Santolaya ME, Ulloa AV, Ponce CA, Cabrera CE, et al. Search for primary infection by Pneumocystis carinii in a cohort of normal, healthy infants. Clin Infect Dis. 2001; 32: 855-861. [CrossRef]
  4. Bishop LR, Kovacs JA. Quantitation of anti-Pneumocystis jiroveci antibodies in healthy persons and immunocompromised patients. Int J Infect Dis. 2003; 187: 1844-1848. [CrossRef]
  5. Peglow SL, Smulian AG, Linke MJ, Pogue CL, Nurre S, Crisler J, et al. Serologic responses to Pneumocystis carinii antigens in health and disease. JID. 1990; 161: 296-306. [CrossRef]
  6. Meuwissen JHET, Tauber I, Leeuwenberg ADEM, Beckers PJA, Sieben M. Parasitologic and serologic observations of infection with Pneumocystis in humans. JID. 1977; 136: 43-9. [CrossRef]
  7. Nevez G, Totet A, Pautard JC, Raccurt C. Pneumocystis carinii detection using nested-PCR in nasopharyngeal aspirates of immunocompetent infants with bronchiolitis. J Eukaryot Microbiol. 2001; Suppl: 122S-123S. [CrossRef]
  8. Roux A, Canet E, Valade S, Gangneux-Robert F, Hamane S, Lafabrie A, et al. Pneumocystis jirovecii pneumonia in patients with or without AIDS, France. Emerging Infect Dis. 2014; 20: 1490-1497. [CrossRef]
  9. Cordonnier C, Cesaro S, Maschmeyer G, Einsele H, Donnelly JP, Alanio A, et al. Pneumocystis jirovecii pneumonia: still a concern in patients with haematological malignancies and stem cell transplant recipients. J Antimicrob Chemother. 2016; 71: 2379-85. [CrossRef]
  10. Koike R, Takeuchi T, Eguchi K, Miyasaka N, Japan College of Rheumatology. Update on the Japanese guidelines for the use of infliximab and etanercept in rheumatoid arthritis. Mod Rheumatol. 2007; 17: 451-458. [CrossRef]
  11. Morris A, Norris KA. Colonization by Pneumocystis jirovecii and its role in disease. Clin Microbiol Rev. 2012; 25: 297-317. [CrossRef]
  12. Liu Y, Fahle GA, Kovacs JA. Inability to culture Pneumocystis jirovecii. [Internet]. Washington: mBio; 2018 [cited 2018 Sep 27]. Available from:
  13. Ma L, Cissé OH, Kovacs JA. A molecular window into the biology and epidemiology of Pneumocystis spp. Clin Microbiol Rev. 2018; 31. [CrossRef]
  14. Cissé OH, Hauser PM. Genomics and evolution of Pneumocystis species. Infect Genet Evol. 2018; 65: 308-320. [CrossRef]
  15. Alanio A, Desnos-Ollivier M, Garcia-Hermoso D, Bretagne S. Investigating clinical issues by genotyping of medically important fungi: why and how? Clin Microbiol Rev. 2017; 30: 671-707. [CrossRef]
  16. Hauser PM. The development of a typing method for an uncultivable microorganism: the example of Pneumocystis jirovecii. Infection, Genetics and Evolution. 2004; 4: 199-203. [CrossRef]
  17. Hauser PM, Blanc DS, Bille J, Francioli P. III. Typing methods to approach Pneumocystis carinii genetic heterogeneity. FEMS Immunol Med Microbiol. 1998; 22: 27-35. [CrossRef]
  18. Ben Beard C, Roux P, Nevez G, Hauser PM, Kovacs JA, Unnasch TR, et al. Strain typing methods and molecular epidemiology of Pneumocystis pneumonia. Emerg Infect Dis. 2004; 10: 1729-1735. [CrossRef]
  19. Olive DM, Bean P. Principles and applications of methods for DNA-based typing of microbial organisms. J Clin Microbiol. 1999; 37: 1661-1669.
  20. van Belkum A, Tassios PT, Dijkshoorn L, Haeggman S, Cookson B, Fry NK, et al. Guidelines for the validation and application of typing methods for use in bacterial epidemiology. Clin Microbiol Infect. 2007; 13: 1-46. [CrossRef]
  21. Alanio A, Gits-Muselli M, Mercier-Delarue S, Dromer F, Bretagne S. Diversity of Pneumocystis jirovecii during Infection revealed by ultra-deep pyrosequencing. [Internet]. Aberdeen: Front Microbiol; 2016 [cited 2018 Sep 25]. Available from:
  22. Gits-Muselli M, Peraldi M-N, de Castro N, Delcey V, Menotti J, Guigue N, et al. New short tandem repeat-based molecular typing method for Pneumocystis jirovecii reveals intrahospital transmission between patients from different wards. PLOS ONE. 2015; 10: e0125763. [CrossRef]
  23. Alanio A, Gits-Muselli M, Guigue N, Desnos-Ollivier M, Calderon EJ, Di Cave D, et al. Diversity of Pneumocystis jirovecii across europe: a multicentre observational study. EBio Medicine. 2017; 22: 155-163. [CrossRef]
  24. Ma L, Kutty G, Jia Q, Imamichi H, Huang L, Atzori C, et al. Analysis of variation in tandem repeats in the intron of the major surface glycoprotein expression site of the human form of Pneumocystis carinii. JID. 2002; 186: 1647-1654. [CrossRef]
  25. Hauser PM, Blanc DS, Telenti A, Nahimana A, Bille J, Francioli P. Potential coinfections complicate typing of Pneumocystis carinii f. sp. hominis. J Clin Microbiol. 1998; 36: 3111.
  26. Hunter PR, Gaston MA. Numerical index of the discriminatory ability of typing systems: an application of Simpson’s index of diversity. J Clin Microbiol. 1988; 26: 2465-2466.
  27. Orita M, Iwahana H, Kanazawa H, Hayashi K, Sekiya T. Detection of polymorphisms of human DNA by gel electrophoresis as single-strand conformation polymorphisms. Proc Natl Acad Sci USA. 1989; 86: 2766-2770. [CrossRef]
  28. Nahimana A, Blanc DS, Francioli P, Bille J, Hauser PM. Typing of Pneumocystis carinii f. sp. hominis by PCR-SSCP to indicate a high frequency of co-infections. J Med Microbiol. 2000; 49: 753-758. [CrossRef]
  29. Ma L, Kovacs JA. Rapid detection of mutations in the human-derived Pneumocystis carinii dihydropteroate synthase gene associated with sulfa resistance. Antimicrob Agents Chemother. 2001; 45: 776-780. [CrossRef]
  30. Hauser PM, Francioli P, Bille J, Telenti A, Blanc DS. Typing of Pneumocystis carinii sp.f. hominis by PCR-SSCP of four genomic regions. J Eukaryot Microbiol. 1997; 44: 16s. [CrossRef]
  31. Ma L, Kovacs JA. Genetic analysis of multiple loci suggests that mutations in the Pneumocystis carinii f. sp. hominis dihydropteroate synthase gene arose independently in multiple strains. Antimicrob Agents Chemother. 2001; 45: 3213-3215. [CrossRef]
  32. Ripamonti C, Orenstein A, Kutty G, Huang L, Schuhegger R, Sing A, et al. Restriction fragment length polymorphism typing demonstrates substantial diversity among Pneumocystis jirovecii isolates. JID. 2009; 200: 1616-1622. [CrossRef]
  33. Sassi M, Ripamonti C, Mueller NJ, Yazaki H, Kutty G, Ma L, et al. Outbreaks of Pneumocystis pneumonia in 2 renal transplant centers linked to a single strain of Pneumocystis: implications for transmission and virulence. Clin Infect Dis. 2012; 54: 1437-1444. [CrossRef]
  34. Ma L, Chen Z, Huang DW, Kutty G, Ishihara M, Wang H, et al. Genome analysis of three Pneumocystis species reveals adaptation mechanisms to life exclusively in mammalian hosts. Nat Commun. 2016; 7: 10740. [CrossRef]
  35. Schmid-Siegert E, Richard S, Luraschi A, Mühlethaler K, Pagni M, Hauser PM. Mechanisms of surface antigenic variation in the human pathogenic fungus Pneumocystis jirovecii. mBio. 2017; 8: e01470-17. [CrossRef]
  36. Rostved AA, Sassi M, Kurtzhals JAL, Sørensen SS, Rasmussen A, Ross C, et al. Outbreak of Pneumocystis pneumonia in renal and liver transplant patients caused by genotypically distinct strains of Pneumocystis jirovecii. Transplantation. 2013; 96: 834-842. [CrossRef]
  37. Helweg-Larsen J, Eugen-Olsen J, Lundgren B. Rapid detection of dihydropteroate polymorphism in AIDS-related Pneumocystis carinii pneumonia by restriction fragment length polymorphism. Scand J Infect Dis. 2000; 32: 481-483. [CrossRef]
  38. Latouche S, Lacube P, Maury E, Bolognini J, Develoux M, Girard P, et al. Pneumocystis jirovecii dihydropteroate synthase genotypes in French patients with pneumocystosis: a 1998–2001 prospective study. Med Mycol. 2003; 41: 533-537. [CrossRef]
  39. Friaza V, Morilla R, Respaldiza N, de la Horra C, Calderón EJ. Pneumocystis jiroveci dihydropteroate synthase gene mutations among colonized individuals and pneumocystis pneumonia patients from spain. J Postgrad Med. 2010; 122: 24-28. [CrossRef]
  40. Le Gal S, Damiani C, Perrot M, Rouillé A, Virmaux M, Quinio D, et al. Circulation of Pneumocystis dihydropteroate synthase mutants in France. Diagn Microbiol Infect Dis. 2012; 74: 119-124. [CrossRef]
  41. Lu JJ, Bartlett MS, Shaw MM, Queener SF, Smith JW, Ortiz-Rivera M, et al. Typing of Pneumocystis carinii strains that infect humans based on nucleotide sequence variations of internal transcribed spacers of rRNA genes. J Clin Microbiol. 1994; 32: 2904-2912.
  42. Lee CH, Helweg-Larsen J, Tang X, Jin S, Li B, Bartlett MS, et al. Update on Pneumocystis carinii f. sp. hominis typing based on nucleotide sequence variations in internal transcribed spacer regions of rRNA genes. J Clin Microbiol. 1998; 36: 734-741.
  43. Nimri LF, Moura INS, Huang L, del Rio C, Rimland D, Duchin JS, et al. Genetic diversity of Pneumocystis carinii f. sp. hominis based on variations in nucleotide sequences of internal transcribed spacers of rRNA genes. J Clin Microbiol. 2002; 40: 1146-1151. [CrossRef]
  44. Wakefield AE. VI. Genetic heterogeneity in human-derived Pneumocystis carinii. FEMS Immunol Med Microbiol. 1998; 22: 59-65. [CrossRef]
  45. Tsolaki AG, Miller RF, Underwood AP, Banerji S, Wakefield AE. Genetic diversity at the internal transcribed spacer regions of the rRNA operon among isolates of Pneumocystis carinii from AIDS patients with recurrent pneumonia. JID. 1996; 174: 141-156. [CrossRef]
  46. Le Gal S, Blanchet D, Damiani C, Guéguen P, Virmaux M, Abboud P, et al. AIDS-related Pneumocystis jirovecii genotypes in French Guiana. Infect Genet Evol. 2015; 29: 60-67. [CrossRef]
  47. Ma L, Huang D-W, Cuomo CA, Sykes S, Fantoni G, Das B, et al. Sequencing and characterization of the complete mitochondrial genomes of three Pneumocystis species provide new insights into divergence between human and rodent Pneumocystis. FASEB J. 2013; 27: 1962-1972. [CrossRef]
  48. Walker DJ, Wakefield AE, Dohn MN, Miller RF, Baughman RP, Hossler PA, et al. Sequence polymorphisms in the Pneumocystis carinii cytochrome B gene and their association with atovaquone prophylaxis failure. JID. 1998; 178: 1767-1775. [CrossRef]
  49. Walker DJ, Meshnick SR. Drug resistance in Pneumocystis carinii: an emerging problem. Drug Resist Updat. 1998; 1: 201-204. [CrossRef]
  50. Edlind TD, Bartlett MS, Weinberg GA, Prah GN, Smith JW. The beta-tubulin gene from rat and human isolates of Pneumocystis carinii. Mol Microbiol. 1992; 6: 3365-3373. [CrossRef]
  51. Mazars E, öDberg-Ferragut C, Dei-Cas E, Fourmaux M-N, Aliouat EM, Brun-Pascaud M, et al. Polymorphism of the thymidylate synthase gene of Pneumocystis carinii from different host species. J Eukaryot Microbiol. 1995; 42: 26-32. [CrossRef]
  52. Lane BR, Ast JC, Hossler PA, Mindell DP, Bartlett MS, Smith JW, et al. Dihydropteroate synthase polymorphisms in Pneumocystis carinii. JID. 1997; 175: 482-485. [CrossRef]
  53. Mei Q, Gurunathan S, Masur H, Kovacs JA. Failure of co-trimoxazole in Pneumocystis carinii infection and mutations in dihydropteroate synthase gene. Lancet. 1998; 351: 1631-1632. [CrossRef]
  54. Takahashi T, Endo T, Nakamura T, Sakashitat H, Kimurat K, Ohnishit K, et al. Dihydrofolate reductase gene polymorphisms in Pneumocystis carinii f. sp. hominis in Japan. J Med Microbiol. 2002; 51: 510-515. [CrossRef]
  55. Ma L, Borio L, Masur H, Kovacs JA. Pneumocystis carinii dihydropteroate synthase but not dihydrofolate reductase gene mutations correlate with prior trimethoprim ‐ sulfamethoxazole or dapsone use. JID. 1999; 180: 1969-1978. [CrossRef]
  56. Denis CM, Mazars E, Guyot K, Odberg-Ferragut C, Viscogliosi E, Dei-Cas E, et al. Genetic divergence at the SODA locus of six different formae speciales of Pneumocystis carinii. Med Mycol. 2000; 38: 289-300. [CrossRef]
  57. Banerji S, Lugli EB, Miller RF, Wakefield AE. Analysis of genetic diversity at the arom locus in isolates of Pneumocystis carinii. J Eukaryot Microbiol. 1995; 42: 675-679. [CrossRef]
  58. Esteves F, Tavares A, Costa MC, Gaspar J, Antunes F, Matos O. Genetic characterization of the UCS and Kex1 loci of Pneumocystis jirovecii. Eur J Clin Microbiol Infect Dis. 2009; 28: 175-178. [CrossRef]
  59. Esteves F, Gaspar J, Tavares A, Moser I, Antunes F, Mansinho K, et al. Population structure of Pneumocystis jirovecii isolated from immunodeficiency virus-positive patients. Infect Genet Evol. 2010; 10: 192-199. [CrossRef]
  60. Keely SP, Baughman RP, Smulian AG, Dohn MN, Stringer JR. Source of Pneumocystis carinii in recurrent episodes of pneumonia in AIDS patients. AIDS. 1996; 10: 881-888. [CrossRef]
  61. Maiden MC, Bygraves JA, Feil E, Morelli G, Russell JE, Urwin R, et al. Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad Sci USA. 1998; 95: 3140-3145. [CrossRef]
  62. Pérez-Losada M, Cabezas P, Castro-Nallar E, Crandall KA. Pathogen typing in the genomics era: MLST and the future of molecular epidemiology. Infect Genet Evol. 2013; 16: 38-53. [CrossRef]
  63. Maitte C, Leterrier M, Le Pape P, Miegeville M, Morio F. Multilocus sequence typing of Pneumocystis jirovecii from clinical samples: how many and which loci should be used? J Clin Microbiol. 2013; 51: 2843-2849. [CrossRef]
  64. Depypere M, Saegeman V, Lagrou K. Typing of Pneumocystis jirovecii by multilocus sequencing: evidence of outbreak? Eur J Clin Microbiol Infect Dis. 2016; 35: 911-916. [CrossRef]
  65. Matos O, Esteves F. Pneumocystis jirovecii multilocus gene sequencing: findings and implications. Future Microbiol. 2010; 5: 1257-1267. [CrossRef]
  66. Desoubeaux G, Dominique M, Morio F, Thepault R-A, Franck-Martel C, Tellier A-C, et al. Epidemiological outbreaks of Pneumocystis jirovecii pneumonia are not limited to kidney transplant recipients: genotyping confirms common source of transmission in a liver transplantation unit. J Clin Microbiol. 2016; 54: 1314-1320. [CrossRef]
  67. Debourgogne A, Favreau S, Ladrière M, Bourry S, Machouart M. Characteristics of Pneumocystis pneumonia in Nancy from January 2007 to April 2011 and focus on an outbreak in nephrology. J Mycol Med. 2014; 24: 19-24. [CrossRef]
  68. Esteves F, Montes-Cano MA, Horra C de la, Costa MC, Calderón EJ, Antunes F, et al. Pneumocystis jirovecii multilocus genotyping profiles in patients from Portugal and Spain. Clin Microbiol Infect. 2008; 14: 356-362. [CrossRef]
  69. Schmoldt S, Schuhegger R, Wendler T, Huber I, Sollner H, Hogardt M, et al. Molecular evidence of nosocomial Pneumocystis jirovecii transmission among 16 patients after kidney transplantation. J Clin Microbiol. 2008; 46: 966-971. [CrossRef]
  70. Gianella S, Haeberli L, Joos B, Ledergerber B, Wüthrich RP, Weber R, et al. Molecular evidence of interhuman transmission in an outbreak of Pneumocystis jirovecii pneumonia among renal transplant recipients. Transpl Infect Dis. 2010; 12: 1-10. [CrossRef]
  71. Pliquett RU, Asbe-Vollkopf A, Hauser PM, Presti LL, Hunfeld KP, Berger A, et al. A Pneumocystis jirovecii pneumonia outbreak in a single kidney-transplant center: role of cytomegalovirus co-infection. Eur J Clin Microbiol Infect Dis. 2012; 31: 2429-2437. [CrossRef]
  72. Esteves F, Gaspar J, de Sousa B, Antunes F, Mansinho K, Matos O. Pneumocystis jirovecii multilocus genotyping in pooled DNA samples: a new approach for clinical and epidemiological studies. Clin Microbiol Infec. 2012; 18: E177-84. [CrossRef]
  73. Nikiforov TT, Rendle RB, Goelet P, Rogers YH, Kotewicz ML, Anderson S, et al. Genetic bit analysis: a solid phase method for typing single nucleotide polymorphisms. Nucleic Acids Res. 1994; 22: 4167-4175. [CrossRef]
  74. Esteves F, Gaspar J, De Sousa B, Antunes F, Mansinho K, Matos O. Clinical relevance of multiple single-nucleotide polymorphisms in Pneumocystis jirovecii pneumonia: development of a multiplex PCR-single-base-extension methodology. J Clin Microbiol. 2011; 49: 1810-1815. [CrossRef]
  75. Esteves F, de Sousa B, Calderón EJ, Huang L, Badura R, Maltez F, et al. Multicentre study highlighting clinical relevance of new high-throughput methodologies in molecular epidemiology of Pneumocystis jirovecii pneumonia. Clin Microbiol Infect. 2016; 22: 566.e9-19. [CrossRef]
  76. Alanio A, Olivi M, Cabaret O, Foulet F, Bellanger A-P, Millon L, et al. Correlation between Pneumocystis jirovecii mitochondrial genotypes and high and low fungal loads assessed by single nucleotide primer extension assay and quantitative real-time PCR. J Eukaryot Microbiol. 2015; 62: 650-656. [CrossRef]
  77. Chang DK, Metzgar D, Wills C, Boland CR. Microsatellites in the eukaryotic DNA mismatch repair genes as modulators of evolutionary mutation rate. Genome Res. 2001; 11: 1145-1146. [CrossRef]
  78. Levinson G, Gutman GA. Slipped-strand mispairing: a major mechanism for DNA sequence evolution. Mol Biol Evol. 1987; 4: 203-221.
  79. Gemayel R, Vinces MD, Legendre M, Verstrepen KJ. Variable tandem repeats accelerate evolution of coding and regulatory sequences. Rev. Genet. 2010; 44: 445-477. [CrossRef]
  80. Garcia-Hermoso D, Desnos-Ollivier M, Bretagne S. Typing candida species using microsatellite length polymorphism and multilocus sequence typing. Methods Mol Biol. 2016; 1356: 199-214. [CrossRef]
  81. de Valk HA, Meis JFGM, Klaassen CHW. Microsatellite based typing of Aspergillus fumigatus: strengths, pitfalls and solutions. J Microbiol Methods. 2007; 69: 268-272. [CrossRef]
  82. Urwin R, Maiden MCJ. Multi-locus sequence typing: a tool for global epidemiology. Trends Microbiol. 2003; 11: 479-487. [CrossRef]
  83. Chiou C-S. Multilocus variable-number tandem repeat analysis as a molecular tool for subtyping and phylogenetic analysis of bacterial pathogens. Expert Rev Mol Diagn. 2010; 10: 5-7. [CrossRef]
  84. Jarboui MA, Mseddi F, Sellami H, Sellami A, Mahfoudh N, Makni F, et al. A comparison of capillary electrophoresis and direct sequencing in upstream conserved sequence region analysis of Pneumocystis jirovecii strains. J. Med. Microbiol. 2013; 62: 560-564. [CrossRef]
  85. Gupta R, Mirdha BR, Guleria R, Kumar L, Luthra K, Agarwal SK, et al. Genetic characterization of UCS region of Pneumocystis jirovecii and construction of allelic profiles of Indian isolates based on sequence typing at three regions. Infect Genet Evol. 2013; 13: 180-186. [CrossRef]
  86. Cisse OH, Pagni M, Hauser PM. De novo assembly of the Pneumocystis jirovecii genome from a single bronchoalveolar lavage fluid specimen from a patient. [Internet]. Washington: mBio; 2012 [cited 2018 Sep 25]. Available from:
  87. Parobek CM, Jiang LY, Patel JC, Alvarez-Martinez MJ, Miro JM, Worodria W, et al. Multilocus microsatellite genotyping array for investigation of genetic epidemiology of Pneumocystis jirovecii. J Clin Microbiol. 2014; 52: 1391-1399. [CrossRef]
  88. Cissé OH, Ma L, Wei Huang D, Khil PP, Dekker JP, Kutty G, et al. Comparative population genomics analysis of the mammalian fungal pathogen Pneumocystis. mBio. 2018; 9. [CrossRef]
  89. Urabe N, Ishii Y, Hyodo Y, Aoki K, Yoshizawa S, Saga T, et al. Molecular epidemiologic analysis of a Pneumocystis pneumonia outbreak among renal transplant patients. Clin Microbiol Infec. 2016; 22: 365-371. [CrossRef]
  90. Charpentier E, Garnaud C, Wintenberger C, Bailly S, Murat J-B, Rendu J, et al. Added value of next-generation sequencing for multilocus sequence typing analysis of a Pneumocystis jirovecii pneumonia outbreak1. Emerg Infect Dis. 2017; 23: 1237-1245. [CrossRef]
  91. Esteves F, Gaspar J, Marques T, Leite R, Antunes F, Mansinho K, et al. Identification of relevant single-nucleotide polymorphisms in Pneumocystis jirovecii: relationship with clinical data. Clin Microbiol Infec. 2010; 16: 878-884. [CrossRef]
  92. Helweg-Larsen J, Lee C-H, Jin S, Hsueh JY, Benfield TL, Hansen J, et al. Clinical correlation of variations in the internal transcribed spacer regions of rRNA genes in Pneumocystis carinii f.sp. hominis: AIDS. 2001; 15: 451-459. [CrossRef]
  93. Matos O, Esteves F. Epidemiology and clinical relevanceof Pneumocystis jirovecii Frenkel, 1976 dihydropteroate synthase gene mutations. Parasite. 2010; 17: 219-232. [CrossRef]
  94. Hauser PM, Nahimana A, Taffe P, Weber R, Francioli P, Bille J, et al. Interhuman transmission as a potential key parameter for geographical variation in the prevalence of pneumocystis jirovecii dihydropteroate synthase mutations. Clin Infect Dis. 2010; 51: e28-33. [CrossRef]
  95. Alanio A, Hauser PM, Lagrou K, Melchers WJG, Helweg-Larsen J, Matos O, et al. ECIL guidelines for the diagnosis of Pneumocystis jirovecii pneumonia in patients with haematological malignancies and stem cell transplant recipients. J Antimicrob Chemother. 2016; 71: 2386-2396. [CrossRef]
  96. de Boer MGJ, de Fijter JW, Kroon FP. Outbreaks and clustering of Pneumocystis pneumonia in kidney transplant recipients: a systematic review. Med Mycol. 2011; 49: 673-680.
  97. Yiannakis EP, Boswell TC. Systematic review of outbreaks of Pneumocystis jirovecii pneumonia: evidence that P.jirovecii is a transmissible organism and the implications for healthcare infection control. J Hosp Infect. 2016; 93: 1-8. [CrossRef]
  98. Robin C, Alanio A, Gits-Muselli M, la Martire G, Schlemmer F, Botterel F, et al. Molecular demonstration of a pneumocystis outbreak in stem cell transplant patients: evidence for transmission in the daycare center. Front Microbiol. 2017; 8: 700. [CrossRef]
  99. Ong YL, Jones FG. A cluster of suspected Pneumocystis carinii pneumonia following intensive chemotherapy in a Belfast haematology unit. Ulster Med J. 1998; 67: 104-109.
  100. Choukri F, Menotti J, Sarfati C, Lucet J, Nevez G, Garin YJF, et al. Quantification and spread of Pneumocystis jirovecii in the surrounding air of patients with Pneumocystis pneumonia. clinical infectious diseases. 2010; 51: 259-265. [CrossRef]
  101. Cushion MT, Linke MJ, Ashbaugh A, Sesterhenn T, Collins MS, Lynch K, et al. Echinocandin treatment of Pneumocystis pneumonia in rodent models depletes cysts leaving trophic burdens that cannot transmit the infection. PLoS ONE. 2010; 5: e8524. [CrossRef]
  102. Hauser PM, Blanc DS, Bille J, Nahimana A, Francioli P. Carriage of Pneumocystis carinii by immunosuppressed patients and molecular typing of the organisms: AIDS. 2000; 14: 461. [CrossRef]
  103. Gigliotti F, Harmsen AG, Wright TW. Characterization of transmission of Pneumocystis carinii f. sp. muris through immunocompetent BALB/c mice. Infect Immun. 2003; 71: 3852-3856. [CrossRef]
  104. Dumoulin A, Mazars E, Seguy N, Gargallo-Viola D, Vargas S, Cailliez JC, et al. Transmission of Pneumocystis carinii disease from immunocompetent contacts of infected hosts to susceptible hosts. Eur J Clin Microbiol Infect Dis. 2000; 19: 671-678. [CrossRef]
  105. Miller RF, Lindley AR, Copas A, Ambrose HE, Davies RJO, Wakefield AE. Genotypic variation in Pneumocystis jirovecii isolates in Britain. Thorax. 2005; 60: 679-682. [CrossRef]
  106. Chabé M, Dei-Cas E, Creusy C, Fleurisse L, Respaldiza N, Camus D, et al. Immunocompetent hosts as a reservoir of pneumocystis organisms: histological and rt-PCR data demonstrate active replication. Eur J Clin Microbiol Infect Dis. 2004; 23: 89-97. [CrossRef]
  107. Durand-Joly I, Soula F, Chabé M, Dalle JH, Lafitte JJ, Senechal M, et al. Long-term colonization with Pneumocystis jirovecii in hospital staffs: a challenge to prevent nosocomial pneumocystosis. J Eukaryot Microbiol. 2003; 50: 614-615. [CrossRef]
  108. Stern A, Green H, Paul M, Vidal L, Leibovici L. Prophylaxis for Pneumocystis pneumonia (PCP) in non-HIV immunocompromised patients. Cochrane Database Syst Rev. 2014; 10: CD005590. [CrossRef]
  109. Montooth KL, Rand DM. The spectrum of mitochondrial mutation differs across species. PLoS Biol. 2008; 6: e213. [CrossRef]
  110. Valero C, Buitrago MJ, Gits-Muselli M, Benazra M, Sturny-Leclère A, Hamane S, et al. Copy number variation of mitochondrial DNA genes in Pneumocystis jirovecii according to the fungal load in BAL specimens. Front Microbiol. 2016; 7: 1413. [CrossRef]
  111. Garcia-Hermoso D, Janbon G, Dromer F. Epidemiological evidence for dormant Cryptococcus neoformans infection. J Clin Microbiol. 1999; 37: 3204-3209.
  112. Alanio A, Vernel-Pauillac F, Sturny-Leclère A, Dromer F. Cryptococcus neoformans host adaptation: toward biological evidence of dormancy. MBio. 2015; 6. [CrossRef]
  113. An CL, Gigliotti F, Harmsen AG. Exposure of immunocompetent adult mice to Pneumocystis carinii f. sp. muris by cohousing: growth of P. carinii f. sp. muris and host immune response. Infect Immun. 2003; 71: 2065-2070. [CrossRef]
  114. Dohn MN, White ML, Vigdorth EM, Ralph Buncher C, Hertzberg VS, Baughman RP, et al. Geographic clustering of Pneumocystis carinii pneumonia in patients with HIV infection. Am J Respir Crit Care Med. 2000; 162: 1617-1621. [CrossRef]
  115. Beard CB, Carter JL, Keely SP, Huang L, Pieniazek NJ, Moura IN, et al. Genetic variation in Pneumocystis carinii isolates from different geographic regions: implications for transmission. Emerging Infect Dis. 2000; 6: 265-272. [CrossRef]
  116. Gigliotti F. Antigenic variation of a major surface glycoprotein of Pneumocystis carinii. J Protozool. 1991; 38: 4S-5S.
  117. Stringer JR. Antigenic variation in Pneumocystis. J Eukaryot Microbiol. 2007; 54: 8-13. [CrossRef]
  118. Leigh TR, Wakefield AE, Peters SE, Hopkin JM, Collins JV. Comparison of DNA amplification and immunofluorescence for detecting Pneumocystis carinii in patients receiving immunosuppressive therapy. Transplantation. 1992; 54: 468-470. [CrossRef]
  119. Mori S, Cho I, Sugimoto M. A followup study of asymptomatic carriers of Pneumocystis jiroveci during immunosuppressive therapy for rheumatoid arthritis. J Rheumatol. 2009; 36: 1600-1605. [CrossRef]
  120. Choukri F, Aliouat EM, Menotti J, Totet A, Gantois N, Garin YJF, et al. Dynamics of Pneumocystis carinii air shedding during experimental Pneumocystosis. J Infect Dis. 2011; 203: 1333-1336. [CrossRef]
  121. Slatkin M. A measure of population subdivision based on microsatellite allele frequencies. Genetics. 1995; 139: 457-462.
  • View
  • Download
Download PDF