Journal of Fungi Review Consensus Multilocus Sequence Typing Scheme for Pneumocystis jirovecii Lana Pasic 1,2,3,† , Lidia Goterris 4,5,† , Mercedes Guerrero-Murillo 4,5 , Laszlo Irinyi 1,2,3 , Alex Kan 1,2,3 , Carolina A. Ponce 6 , Sergio L. Vargas 6 , M. Teresa Martin-Gomez 4,5 and Wieland Meyer 1,2,3,7, * 1 Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Clinical School, Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney 2006, Australia; lana.pasic@sydney.edu.au (L.P.); laszlo.irinyi@sydney.edu.au (L.I.); alex.kan@sydney.edu.au (A.K.) 2 Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney 2006, Australia 3 Westmead Institute for Medical Research, Westmead 2145, Australia 4 Microbiology Department, Hospital Universitari Vall d’Hebron (VHUH), 08035 Barcelona, Spain; lgoterris@vhebron.net (L.G.); mercedes.guerrero@vhir.org (M.G.-M.); mtmartin@vhebron.net (M.T.M.-G.) 5 Genetics and Microbiology Department, Universitat Autònoma de Barcelona (UAB), 08035 Barcelona, Spain 6 Instituto de Ciencias Biomédicas (ICBM), Facultad de Medicina, Universidad de Chile, Santiago de Chile 8380453, Chile; cponce@med.uchile.cl (C.A.P.); svargas@med.uchile.cl (S.L.V.) 7 Westmead Hospital (Research and Education Network), Westmead 2145, Australia * Correspondence: wieland.meyer@sydney.edu.au; Tel.: +61-2-86273430 † These authors contributed equally to this work.  Received: 10 September 2020; Accepted: 18 October 2020; Published: 30 October 2020  Abstract: Pneumocystis jirovecii is an opportunistic human pathogenic fungus causing severe pneumonia mainly in immunocompromised hosts. Multilocus sequence typing (MLST) remains the gold standard for genotyping of this unculturable fungus. However, the lack of a consensus scheme impedes a global comparison, large scale population studies and the development of a global MLST database. To overcome this problem this study compared all genetic regions (19 loci) currently used in 31 different published Pneumocystis MLST schemes. The most diverse/commonly used eight loci, β-TUB, CYB, DHPS, ITS1, ITS1/2, mt26S and SOD, were further assess for their ability to be successfully amplified and sequenced, and for their discriminatory power. The most successful loci were tested to identify genetically related and unrelated cases. A new consensus MLST scheme consisting of four genetically independent loci: β-TUB, CYB, mt26S and SOD, is herein proposed for standardised P. jirovecii typing, successfully amplifying low and high fungal burden specimens, showing adequate discriminatory power, and correctly identifying suspected related and unrelated isolates. The new consensus MLST scheme, if accepted, will for the first time provide a powerful tool to investigate outbreak settings and undertake global epidemiological studies shedding light on the spread of this important human fungal pathogen. Keywords: P. jirovecii; consensus MLST scheme; β-TUB; CYB; mt26S and SOD 1. Introduction Pneumocystis jirovecii is a major opportunistic pathogen, which can manifest into severe pneumonia, Pneumocystis pneumonia (PCP), in immunocompromised patients. PCP can cause interstitial lung disease, along with fever, coughs and dyspnea [1]. The incidence is still relatively high, especially in the developing world, for this underestimated fungus, with reported mortality rates ranging from J. Fungi 2020, 6, 259; doi:10.3390/jof6040259 www.mdpi.com/journal/jof J. Fungi 2020, 6, 259 2 of 20 10% to 60% [2,3]. Besides causing isolated cases, P. jirovecii has been linked to nosocomial outbreaks affecting mainly solid organ transplant recipients with devastating consequences. Besides helping to establish epidemiological links among affected patients, allowing for paths of transmission to be mapped and index cases identified within hospital outbreaks, genotyping is an essential tool to achieve knowledge on more general aspects of the epidemiology of microorganisms. Multilocus sequence typing (MLST) is currently the preferred standard for genotyping, due to the limited amounts of DNA being available from this unculturable fungus in clinical samples, its reproducibility, inexpensiveness and discriminatory ability [4]. However, unlike many other human pathogenic fungi, Pneumocystis has, as yet, no consensus typing scheme, which hinders the ability for global comparison of clinical isolates, since multiple various typing schemes are currently in use [5]. There are 19 coding and non-coding DNA regions which have been explored for Pneumocystis genotyping world-wide. The levels of allelic polymorphism fluctuate greatly between the used DNA regions, resulting in varying levels of discriminatory power among 31 schemes currently reported in the literature (see Table 1) [3,5–71]. The lack of standardisation limits the interpretation and comparison of different epidemiological datasets and studies. Molecular typing of P. jirovecii is further hampered by the fact that the fungus cannot be cultured in vivo, and hence the volume of DNA available for sequencing analysis is limited [72]. The DNA volume can be further depleted depending on the source and site of extraction, and if the patients are having a mild infection or if they are colonised carriers [73]. Therefore, the ability of a locus to be successfully amplified is equally as important as it is discriminatory power, when deliberating which loci to include in a standardised MLST scheme. J. Fungi 2020, 6, 259 3 of 20 Table 1. Published genetic loci used in P. jirovecii genotyping, corresponding multilocus sequence typing (MLST) schemes and obtained allele and sequence types. MLST schemes described are listed chronologically, followed by the respective publications using the specific scheme. The third column indicates the total number of isolates included in the study, followed by the fourth column, which indicates the number of isolates which were able to be successfully sequenced by the study. The fifth column lists the total number of sequence types identified, with the following columns listing the number of allele types found for each genetic locus. Schemes # of # of Genetic Locus (Included Country Total # of Samples Sequence Loci) and Samples Sequenced Types arom/ Reference 5.8S 18S 23S 26S ITS1 ITS2 ITS1/2 msg mt26S β-TUB TS mtSSU DHPS UCS Kex1 CYB SOD DHRF TRR1 EPSP Scheme 1 (5.8S, 18S, 26S, ITS1, ITS2) [6] USA 15 15 6 1 1 1 2 3 NG [7] GBR 24 24 NG 1 1 1 5 7 NG Scheme 2 (ITS1, ITS2, msg, mt26S) [8] USA 15 15 NG NG NG NG NG [38] IND 180 29 NG NG NG NG NG Scheme 3 (26S, β-TUB, ITS1, mt26S) [9] CHE 11 11 NG 3 3 3 2 [20] EUR 212 212 6 6 3 4 3 [19] EUR 91 91 28 NG NG NG NG [33] DEU 7 7 2 NG NG NG NG [42] DEU 20 14 NG 2 4 4 1 [43] CHE 19 7 1(+) 2 4 3 2 [50] DE 18 18 NG 2 3 3 2 [53] GBR 670 31 NG NA 5 4 NA [54] FRA 13 10 3 2 2 3 1 Scheme 4 (ITS1, ITS2, mt26S) [10] USA 15 15 6 4 3 7 4 SWE, [11] 7 7 NG 4 4 NG 3 FRA [48] GBR 27 27 NG NG NG 2 3 Scheme 5 (5.8S, ITS1, ITS2, mt26S, TS) FRA, [12] 20 18 NG 6 3 3 10 4 1 ITA Scheme 6 (arom, ITS1, ITS2, mt26S, mtSSU) [13] NLD 6 6 NG NG NG 9 3 1 2 Scheme 7 (ITS1, ITS2) [14] GLO 207 207 NG 15 14 NG [18] JPN 24 24 NG 11 11 NG [31] ZAF 20 20 NG 11 13 NG [49] SWE 64 64 12 10 12 NG 4 4 4 4 4 4 4 4 9 6 3 6 6 5 3 ⌘ J. Fungi 2020, 6,3 259 7 4 3 ⌘ 4 of 20 2 2 1 2 1 1 G NG NG Table 1. Cont. 5 3 4 2 Schemes 1 7 #3 of 3 # of Genetic Locus (Included Country Total # of Samples Sequence Loci) and Samples Sequenced Types arom/ G Reference 5.8S 18S 23S 26S ITS1 ITS2 ITS1/2 msg mt26S β-TUB TS mtSSU DHPS UCS Kex1 CYB SOD DHRF TRR1 EPSP G Scheme 8 (DHPS, ITS1, ITS2, NG mt26S) NG 4 2 [15] FRA 14 4 2 14 2 NG NG NG NG NG NG 6 [39] PRT, ESP 108 5 3 # NG 12 10 NG 4 4 2 14 4 [44] AUS 68 68 NG 8 9 16 2 2 4 3 2 3 Scheme 9 (DHFR, DHPS) 6 2 1 [16] USA 37 5 237 NG 4 2 4 [32] FRA 33 5 333 NG 3 2 5 9 3 [40] THA 29 18 NG 3 3 [71] 1 USA 13 13 NG 2 2 [70] COL 98 45 NG 4 2 3 3 2 Scheme 10 (DHPS, mt26S) 3 [17] 1 USA 324 3 2191 14 4 4 gated in this study, but not [26] includedESP in the newly 255 proposed 79 MLSTNG 4 4 [34] notESPgiven; NA50 12 NG 4 1 ST scheme. NG = Information [35] USA 442 Z = No amplification NG 4 4 d when the controls are [45]included.ESP ✕ = 91 samples 60 amplified 19 for NG 3 1 al large ribosomal subunit [51] (mt26S) and ITA 53% for 67 DHPS; ⚑ = 67 for NG 4 3 Scheme D) 74%, β-tubulin (β-TUB) 11 (26S, 49%, β-TUB, DHPS, dihydrofolate ITS1, mt26S) reductase gene (DHFR) [21] USA 22 22 10 2 5 4 2 3 uence divergence, not included in study further for genotyping; ^ = Scheme 12 (26S, β-TUB, ITS1, ITS2, mt26S) Country codes are according [22] to ISO ITA3166-1 alpha-3. 25 18 15 4 6 6 4 3 Scheme 13 (DHPS, ITS1, ITS2) [23] USA 57 37 NG 6 7 NG 3 [27] PRT 43 43 NG 15 14 17 2 [36] ITA 261 174 NG NG NG 9 3 Scheme 14 (CYB, DHFR, DHPS) [24] JPN 34 34 NG 4 2 1 Scheme 15 (DHPS, ITS1, ITS2, mtSSU) [25] GBR 2 2 NG NG NG 2 1 1 Scheme 16 (DHPS, mt26S, mtSSU) GBR, [28] 51 30 NG 3 4 2 ZWE Scheme 17 (DHPS, mtSSU, mt26S, SOD) [29] GBR 16 16 NG NG NG NG NG [30] NG 76 76 15 4 4 4 4 USA 57 37 Scheme NGβ-TUB, CYB, DHFR, DHPS, ITS1, mt26S, SOD) 24 (26S, 6 7 NG 3 Scheme Scheme 15 (DHPS, ITS1, 25 mtSSU) ITS2, (26S, ITS1, ITS2, mt26S) Scheme 25 (26S, ITS1, ITS2, mt26S) PRT 43 43 NG 15 14 NG 17 9 2 [5] [25] FRA [56]GBR 23 2DNK 23 2 22 18NG 3 [56] 7 DNK NG NG NG 22NG 2 NG 418 NG 2 3 NG 1 1 1 NG NG 7 NG 3 NG 3 NG ITA 261 174 Scheme NG 25 (26S, NG NG 9 3 Scheme 16ITS1, (DHPS,ITS2, mt26S) Scheme mt26S, 26 (CYB, ITS1, mt26S, SOD) mtSSU) Scheme 26 (CYB, ITS1, mt26S, SOD) R, DHPS) [56] [28] DNK [58]ZWE GBR, 22 51FRA 18 30 37 3 32NG NG [58] NG NG FRANG NG 37NG NG32 3 NGNG 4 2 NG NG NG NG JPN 34 34 Scheme NG 26 (CYB, ITS1, mt26S, SOD) 4 2 1 Scheme 17 (DHPS, Scheme mtSSU, 27 (β-TUB, mt26S, SOD)CYB, DHFR, mt26S, SOD) Scheme 27 (β-TUB, CYB, DHFR, mt26S, SOD) 1, ITS2, mtSSU) NG NG [58] [29] FRA [59]GBR 37 16BEL 32 16 20 NG20 NG ^ NG [59] BEL 20NA 20 ^ NG NG 4 2 NG NG NA NG NG NG 4 42 2 GBR 2 2 NG Scheme 27 (β-TUB, NG NG 2 1 1 [30] CYB, DHFR, Scheme mt26S, 28 NG SOD) (CYB, mt26S, SOD) 76 76 15 Scheme 28 (CYB, mt26S, SOD) 4 4 4 4 6S, mtSSU) [59] BEL [60] Scheme 18 (DHFR, DHPS, ITS1, ITS2) 20 FRA 20 ^ 24 NG ◎ 14 [60] NA FRA 24 4◎ 2 14 6 4 2 2 5 63 GBR, ZWE 51 30 NG 3 4 2 SU, mt26S, SOD) J. Fungi 2020, 6, 259 Scheme 28 (CYB, [37] mt26S, SOD) [61] PRT 68FRA 68 32 32NG 18 [61] FRA NG NG 3219 32 18 22 4 5 of 20 14 4 224 [60] ◎ 67 5 3 Scheme 19 (UCS, Kex1)FRA [62] 24 FRA 7 14 7 NG [62] FRA 7 NG 4 3 42 GBR 16 16 [61] NG NG NG NG 22 NG 14 4 NG 76 76 [62] [39] 15 FRA [63] FRA PRT 32 7 87POL 32 7 35 17 18 NG ◉ NG 8 4 [63] POL 4 17 4 ◉ 4 8 13 4 4 4 3 2 6 132 Scheme 20 (CYB, DHFR, DHPS, [66] mt26S, SOD) FRA 192 35 17 [66] FRA 192 35 17 11 5 112 PS, ITS1, ITS2) [63] [46] POL [67] PRT 17 102 TUR ◉ 78 31 8 26NG 6 [67] TUR 314 1326 9 6 4 6 6 3 2 6 65 43 PRT 68 68 [66] Scheme NG 21 (β-TUB, CYB, FRA DHFR, 192REU,TRR1, [68] DHPS, mt26S, GUF,TS, FRA 35 SOD) NG 47 NG 17 47 19 23 Table 1. Cont. [68] REU, GUF, FRA 47 1147 23 5 4 5 2 9 53 [67] [47] TUR 29 Scheme PRT(23S, 26S, 31 DHPS)70 26 ► 6 48 Scheme 29 (23S, 26S, DHPS) 4 5 3 ⌘ 3 5 7 3 4 3 ⌘ PRT 87 35 NG 4 4 [68] REU, GUF,ITS1/2, FRA mt26S)47 47 23 30 530 1 9 3 R, DHPS, mt26S, SOD) Schemes Scheme 22 (β-TUB, DHPS, [64] # of 11 BRA # of11 30 5 [64] BRA 3 2 30 Genetic Locus 5 3 2 Scheme 29 (23S, [3] 26S, DHPS) Scheme 30 (DHFR, DHPS, mt26S) Scheme 30 (DHFR, DHPS, mt26S) PRT 102 (Included 78 NG Country Total AUS # of Samples Sequence 2 9 4 6 2 3 2 6 6 1 [64] BRA 30 30 5 37 4 3 [65] 2 37 2 37 2 1 B, DHFR, DHPS, mt26S, TRR1, TS, SOD)Loci) and [55] Samples AUS [65] Sequenced 48IND 48 37 13 IND arom/1 13 3 1 3 3 2 Reference Scheme 30 (DHFR, [57] DHPS, Scheme mt26S) AUS31 (CYB, DHPS, mt26S,7 SOD)Types7 5.8S 18SNG 23S 26S ITS1 SchemeITS2 31 (CYB, ITS1/2 SOD) mt26SNG β-TUB TS NG DHPS, mt26S,msg NG mtSSU DHPS UCS Kex1 NG CYB SOD DHRF TRR1 PRT 70 ► 48 5 3 ⌘ 3 EPSP 7 4 3 ⌘ [65] Scheme IND [69] 23 (mt26S, mtSSU) 37 POL 37 72 13 N/A N/A [69] POL 72 3 N/A N/A3 3 1 2 3 32 PS, ITS1/2, mt26S) SchemeScheme18 (DHFR, [52]DHPS, 31 (CYB, ITS1, DHPS, mt26S, FRA,SOD)ITS2) CUB, ESP 75 75 NG 5 3 4 AUS AUS 11 48 11 48[37] [69]PRT Scheme 2 Loci in black did not match diversity 24 (26S, β-TUB, 4 POL 68CYB, DHFR, DHPS, 72 68ITS1, mt26S,N/A N/A 2 criteria for22 further SOD) NG 2 NG 1Lociconsideration. NG in black 19 did Loci not match 1 in blue 1 diversity indicate 3 criteria loci investigated for further4inconsideration. this study, 1 but Loci notinincluded blue43indicate in 2thelocinewly investigated proposed in MLSth [5] FRA 23 NG 23 7 9 4 2 1 7 3 3 AUS 7 7 Scheme Loci in black did NG Scheme Kex1) 19 (UCS, not match scheme. Loci diversity in green criteria 25 (26S, ITS1, ITS2, mt26S) indicatefor further lociNG consideration. suggested from this NG NG Loci scheme. studyinLoci blue inindicate for the green loci newlyindicate investigated proposed NG lociconsensus in thisMLST suggested study,this from butstudy scheme. not NGincluded for= the in the newly Information newly not proposed proposed given; NAMLST consensus = No MLST amplificatio scheme SU) FRA, CUB, ESP 75 75[39] PRT[56] scheme. Loci inrecorded; NG 87 DNK green indicate and 1(+) Scheme 26 (CYB, ITS1, mt26S, SOD) 35 22 loci= suggested Study onlyfrom 3 listed NG 18 this thestudy 5 for the sequence newly recorded; types NG (STs) forNG proposed and test =NG 1(+) NG consensus 3isolates, Study onlyMLST 5 ST NG listed were scheme. the identifiedNG when sequence = Information types 4 the(STs) 4 test not controls for given; are NA =5No included. isolates, ✕ ST= amplification were 91 samples identified amplified when the f Scheme 20 (CYB, DHFR, DHPS, mt26S, SOD) , CYB, DHFR, DHPS, ITS1, mt26S, SOD) FRA 23 23 [46] recorded; and dihydropteroate PRT [58] NG 1(+) = Study only FRA listed(DHPS) synthase 102DHFR, mt26S, SOD) the sequence 78 37 andNG68 types 7 NG 32 (STs) for Internal 9 4 for test isolates, Transcribed 2dihydropteroate 5NG Spacer ST(ITS); were synthase 9 ❋identified (DHPS) 1= 100% and when for 68 NG the controls mitochondrial for 7Internal 3 3 are large Transcribed 6 included. ribosomal Spacer ✕ subunit = 91 (ITS); 3 ❋ samples (mt26S) 6 = and 100% 6 amplified 53% NG for for for mitochondrial NG DHPS; ⚑ = large67 ribo f Scheme 27 (β-TUB, CYB, ❋21 4 ⚑ 2= reductase TS2, mt26S) DNK 22 Scheme 18 dihydropteroate mt26S [59] synthase (DHPS) and 21 for and BEL 21 (β-TUB,3 CYB, DHFR, DHPS, mt26S, TRR1, DHPS; ► =Internal 68 for mt26SNG 20 NG NG Transcribed 100%, 20 NGTS, SOD) ^ NG NG Spacer cytochrome (ITS); bmt26S oxidaseandgene = 100% (CYB) for NA DHPS; for 61%, ► mitochondrial superoxide large = mt26S dismutase 100%, 4 ribosomal cytochrome 2 (SOD) subunit 74%, b oxidase (mt26S) β-tubulin and gene (β-TUB) (CYB) 53% forsuperoxide 61%, 49%, DHPS; dihydrofolate 67 2for dismutase (SOD) gene74%, (DHFRβ- Scheme 28 (CYB, mt26S, SOD) mt26S, SOD) FRA 37 32 [47] mt26S and 21 for PRT[60] NG DHPS; 91%, DHPS 70 ►96%, = mt26S FRA 100%, cytochrome thioredoxin 24 b oxidase reductase14 gene 48 ◎(Trr1) NG NG gene and(CYB) 61%, superoxide thymidylate 91%, DHPS synthase dismutase 96%, thioredoxin gene (SOD) 5 (TS)reductase 336%; ⌘ gene 6= 74%, Null NG β-tubulin (Trr1) and(β-TUB) sequence NG thymidylate 49%,synthase divergence, 3 dihydrofolate not included 7 gene reductase 4 (TS) in 3study 36%; ⌘ 5 gene =3 (DHFR) furtherNullforsequence genotyping; diver^ reductase◎gene ◉= ⌘◎mt26S ◉ study = [61] FRA 32 18 32 22 14 4 B, DHFR, mt26S, SOD) Scheme 22 (β-TUB, 91%, DHPS 96%, ITSthioredoxin no amplification; [62] DHPS, ITS1/2, FRAmt26S) (Trr1) = 78% SOD, 7 and96.4% NG thymidylate mt26S and 7 synthase 82.1%gene ITS no CYB; (TS) 36%; amplification; 17/17 == Null 78%and sequence SOD,CYB,96.4% divergence, 4 5/17 mt26S SOD. and not Country included 82.1% codes CYB;arein further according 17/17 mt26S for to ISOandgenotyping; 3166-1 3CYB,2alpha-3. ^ = Country co 5/17 SOD. BEL 20 20 ^ NG NA 4 2 4 2 2 S, SOD) [3] ITS no amplification; ◎ = 78% SOD, 96.4% AUS[63] 11 POL ◉ 11 17 mt26S and 8 82.1% CYB; ◉ = 17/17 mt26S 2 4 and CYB,2 5/17 SOD. 2 13 Country 1 codes are according to ISO 3166-1 alpha-3. 6 2 FRA 24 ◎[55] AUS[66] 14 48 FRA 48 192 4 35 17 6 2 2 1 11 5 3 1 5 2 FRA 32 32 [67] 18 TUR 31 26 6 22 4 14 4 5 3 [57] AUS[68] 7 REU, GUF, FRA 7 47 NG 47 23 NG NG NG 5 NG 9 3 FRA 7 7 NG 4 3 2 POL 17 Scheme 23 (mt26S, ◉ Scheme 29 8 mtSSU) (23S, 26S, DHPS) 13 6 2 [64] BRA 30 30 5 3 2 1 FRA 192 35 FRA, 17 11 5 2 Scheme 30 (DHFR, DHPS, mt26S) TUR 31 26[52] CUB, 6 75 75 NG 4 5 5 33 [65] ESP23 IND 37 37 13 3 3 2 REU, GUF, FRA 47 47 5 9 3 Scheme 31 (CYB, DHPS, mt26S, SOD) HPS) Scheme 24 (26S, β-TUB, [69] CYB, DHFR, POL DHPS, ITS1, 72 mt26S,N/A SOD) N/A 3 1 3 2 BRA 30 30 5 3 2 1 PS, mt26S) [5] FRA 23 23 NG 7 9 4 2 1 7 3 3 Loci in black did not match diversity criteria for further consideration. Loci in blue indicate3 loci investigated in this study, but not included in the newly proposed MLST IND 37 37 Scheme 25 (26S, ITS1,13 ITS2, mt26S) 3 2 S, mt26S, SOD) scheme. Loci in green indicate loci suggested from this [56] DNK 22 18study NG 3 NG for the NG newly 3 NG proposed consensus NG 1 MLST scheme. NG = Information not given; NA = No amplification POL 72 N/A N/A 3 2 recorded; Scheme 26 (CYB, and ITS1, mt26S, 1(+) = Study only listed the sequence types (STs) for test isolates, 5 ST were identified when the controls are included. ✕ = 91 samples amplified for SOD) ck did not match diversity criteria for further consideration. Loci in blue indicate loci investigated in this study, but not included in the newly proposed MLST [58] FRA 37 synthase dihydropteroate 32 (DHPS) NG NG Spacer (ITS); ❋ = 100% and 68 for Internal Transcribed NGfor mitochondrial large ribosomal subunit (mt26S) NG NG for DHPS; ⚑ = 67 for and 53% oci in green indicate loci suggested Scheme 27 (β-TUB,from CYB, this DHFR, study mt26S,for SOD)the newly proposed consensus MLST scheme. NG = Information not given; NA = No amplification mt26S and 21 for DHPS; ► = mt26S 100%, cytochrome b oxidase gene (CYB) 61%, superoxide dismutase (SOD) 74%, β-tubulin (β-TUB) 49%, dihydrofolate reductase gene (DHFR) and 1(+) = Study only listed [59] the sequence BEL types 20 (STs) 20for ˆ test isolates, NG 5 ST were identified when NA the controls are included. 4 ✕2 = 91 samples amplified for 4 2 2 91%, SOD)96%, thioredoxin reductase gene (Trr1) and thymidylate synthase gene (TS) 36%; ⌘ = Null sequence divergence, not included in study further for genotyping; ^ = DHPS oate synthase (DHPS) and 68 for Internal Transcribed Spacer (ITS); ❋ = 100% for mitochondrial large ribosomal subunit (mt26S) and 53% for DHPS; ⚑ = 67 for Scheme 28 (CYB, mt26S, [60] ITS FRAno amplification; 24 ◎ = 78% SOD, 14 96.4% mt26S and 82.1% CYB; ◉ = 17/17 mt26S and CYB, 6 5/17 SOD. Country codes are according to ISO 5 3166-1 3 alpha-3. 21 for DHPS; ► = mt26S 100%, cytochrome b oxidase gene (CYB) 61%, superoxide dismutase (SOD) 74%, β-tubulin (β-TUB) 49%, dihydrofolate reductase gene (DHFR) [61] FRA 32 32 18 22 14 4 S 96%, thioredoxin reductase gene (Trr1) [62] FRA and thymidylate 7 synthase 7 NG (TS) 36%; ⌘ = Null sequence divergence, not included gene 4 in study further for genotyping; ^ = 3 2 plification; ◎ = 78% SOD,[63] 96.4% mt26SPOL and 82.1% 17 CYB; ◉ = 17/17 mt26S 8 and CYB, 5/17 SOD. Country codes are according13to ISO 3166-1 alpha-3. 6 2 [66] FRA 192 35 17 11 5 2 [67] TUR 31 26 6 4 5 3 REU, [68] GUF, 47 47 23 5 9 3 FRA Scheme 29 (23S, 26S, DHPS) [64] BRA 30 30 5 3 2 1 Scheme Scheme 24 (26S, β-TUB, 24 (26S, CYB, DHFR, β-TUB, CYB,DHPS, DHFR,ITS1, DHPS,mt26S, ITS1,SOD) mt26S, SOD) 5 3 Scheme 24 (26S, β-TUB, CYB, DHFR, DHPS, ITS1, mt26S, SOD) NG 5 3 [5] [5] FRA FRA 23 23 23 23 NG NG 7 79 9 4 4 2 2 [5] FRA 23 23 NG 7 9 Scheme Scheme 25 (26S, ITS1, ITS2, 25 (26S, mt26S) ITS1, ITS2, mt26S) 7 9 4 2 1 7 3 3 Scheme 25 (26S, ITS1, ITS2, mt26S) 9 4 2 [56] 1 [56] DNK DNK 7 3 22 22 18 18 3 3 NG NG NG NG NG NG NG NG NG NG NG 7 3 [56] DNK 22 18 3 NG NG NG N Scheme Scheme 26 (CYB,26ITS1, (CYB,mt26S, ITS1,SOD) mt26S, SOD) NG NG NG NG NG Scheme 26 (CYB, ITS1, mt26S, SOD) [58] [58] FRA FRA 37 37 32 32 NG NG NG NG NG NG 3 NG NG NG NG NG [58] FRA 37 32 NG NG Scheme Scheme 27 (β-TUB, CYB, DHFR, 27 (β-TUB, CYB,mt26S, DHFR,SOD) mt26S, SOD) NG NG NG [59] NG [59] Scheme 27 (β-TUB, CYB, DHFR, mt26S, SOD) NG NG BEL NG BEL NG20 20 20 ^ 20 ^ NG NG NA NA 4 4 2 2 NG [59] BEL 20 20 ^ NG NA Scheme Scheme 28 (CYB,28mt26S, (CYB,SOD) mt26S, SOD) NA J. Fungi 2020, 6, 259 4 2 4 [60] 2 [60] 2 FRA 4FRA Scheme 28 (CYB, mt26S, SOD) ◎ ◎ 6 of 206 NG NA 4 2 2 24 24 2 [60] FRA 14 14 24 ◎ 14 6 [61] [61] FRA FRA 32 32 32 32 18 18 22 22 6 5 [61] FRA 32 32 18 [62] 3 [62] FRA FRA 7 7 7 7 NG NG 4 4 14 22 6 14 4 5 3 [62] FRA 7 7 NG 18 4 22 3 [63] 2 [63] POL 14POL 4 17 17 ◉ [63] ◉ POL 8 8 17 ◉ 8 13 13 NG 13 4 6 [66] 2 [66] Table 1. Cont. FRA 3FRA 2192 192 [66] 35 35 FRA 17 17 192 35 17 11 11 8 13 [67] [67] TUR 6TUR 2 31 31 26 26 6 6 4 4 11 5 [67] TUR 31 26 6 [68] 2 [68] REU, GUF, FRA REU, GUF, FRA 47 47 47 47 23 23 5 5 17 11 5 2 [68] REU, GUF, FRA 47 47 23 Schemes 4 # of 4 # of 5 3 Scheme Scheme 29 (23S, 26S, DHPS) 29 (23S, 26S, DHPS) Genetic Locus 6 5 3 Scheme 29 (23S, 26S, DHPS) (Included 5 Total # of 9 [64] 3 BRA 9BRA 23 Country Samples5 Sequence [64] 3 30 30 [64] 30 30 BRA 5 5 3 3 2 2 Loci) and Samples Sequenced Types Scheme Scheme arom/ 30 30 5 3 2 Reference 1 5.8S 18S 23S 26S 30 (DHFR, ITS1 30 DHPS, (DHFR,mt26S) ITS2DHPS,ITS1/2 mt26S) msg Scheme mt26S β-TUB 30 (DHFR, DHPS, TS mt26S) mtSSU DHPS UCS Kex1 CYB SOD DHRF TRR1 5 3 2 3 2 [65] 1 [65] IND IND 37 37 37 37 13 EPSP13 3 3 [65] IND 37 37 13 Scheme 30 (DHFR, DHPS, mt26S) Scheme Scheme 31 (CYB,31DHPS, (CYB,mt26S, DHPS,SOD) mt26S, SOD) 3 3 Scheme 31 (CYB, DHPS, mt26S, SOD) 13 3 [69] 3 [69] 2 POL POL 72 72 2 N/A N/A N/A N/A 3 3 [65] IND 37 37 13 3 [69] POL 72 3N/A N/A 2 N/A 3 Scheme31 (CYB, DHPS, mt26S, SOD) 3 1 Loci 1 3 in black 2Loci did not in black did 3 match not2 diversity matchLoci in criteria diversityblack fornot criteria did further formatch consideration. further Loci Loci consideration. diversity criteria in blue for indicate in blue further loci investigated indicate Loci in in loci investigated consideration. blue this in study, this stu indicate eration. Loci in blue indicate [69] loci investigated POL 72in this study, N/A but not N/Aincluded in the newly scheme. proposed scheme. a for further consideration. Loci in blue indicate loci investigated in this study, but not included in the newly proposed MLST MLST Loci in Loci green in indicate green 3loci suggested indicate loci suggestedfrom this from study this for 1 the study for newly the proposed newly 2 consensus 3 proposed scheme. Loci in green indicate loci suggested from this study for the newly proposed con consensusMLST scheme. MLST NG scheme. =NG I for the newly proposed ed from this study for the consensus Loci in black MLST did not scheme. NG match diversity = Information criteria not for further newly proposed consensus MLST scheme. NG = Informationrecorded; given; NA consideration. = No Loci inamplification blue indicate notrecorded; given;andNA loci 1(+) and= No investigated =1(+) Study only = Study in this study, listedlisted only recorded; amplification the but not andsequence the included 1(+)sequence in typestypes = Study the newly (STs)listed only proposed for test (STs) MLST for isolates, the test scheme. 5 types isolates, sequence ST 5were ST Loci in identified were (STs) test when foridentified the5 controls when isolates, the wer ST con green indicate loci suggested from this study for the newly proposed consensus MLST scheme. NG = Information not given; NA = No amplification recorded; and 1(+) = Study only ✕ = ❋ ❋ s) for test isolates, 5 ST were sequence types (STs) forlisted identified test isolates, when 5 STtypes the sequence werethe controls identified (STs) are included. when the for test isolates, 5 STcontrols 91 samples when the✕ are included. were identified amplified dihydropteroate = 91are controls for synthase dihydropteroate samples included. (DHPS) synthase (DHPS) amplified = 91 and # 68 and for dihydropteroate for samples 68 Internal for amplified Transcribed Internal synthase Transcribed Spacer (DHPS) andsynthase for dihydropteroate (ITS); Spacer (ITS); 68 for Internal (DHPS) and = 100%= for 100% Transcribed mitochondrial for 68 for Internal large mitochondrial ribosomal large Spacer (ITS); ❋ = 100% for sub ribosoma Spacer (ITS); ❋ = 100% nternal Transcribed Spacer for mitochondrial (ITS); ❋Spacer Transcribed = 100%large ribosomal Zsubunit (mt26S) = 100% for mitochondrial for mitochondrial (ITS); large ribosomal and 53% for DHPS; subunitsubunit large ribosomal (mt26S) mt26S ⚑ and and (mt26S) = and mt26S 67 21 and 53%53% for for 21 for for DHPS; for DHPS;► DHPS; ⚑ ==6767 DHPS; = ► mt26S= mt26S 100%, mt26S forfor mt26Sand cytochrome 100%, and 2121for b cytochrome oxidase b DHPS; ► = mt26S forDHPS; gene oxidase (CYB) gene mt26S100%, 100%, 61%, (CYB) superoxide 61%, cytochrome cytochrome dismutase superoxide b oxidase b oxidase (SOD) dismutase gene gene 74%, (SOD) β-tubulin 74%, (CYB) (CYB) 61%, superoxide dis (β β-tubu ene (CYB) 61%, superoxide ytochrome b oxidase gene (CYB) dismutase 61%, superoxide (SOD) 74%, dismutase 61%, superoxide β-tubulin (SOD) 74%, dismutase (β-TUB) β-tubulin (SOD) 49%, 74%,(β-TUB) dihydrofolate reductase dihydrofolate 49%,(β-TUB) β-tubulin 91%, gene 49%,reductase DHPS 91%, (DHFR) 96%, DHPS gene (DHFR) dihydrofolate thioredoxin 96%, reductase 91%, gene reductase thioredoxin DHPS gene reductase 96%, thioredoxin 91%, (DHFR) DHPS 96%, (Trr1) gene and (Trr1) reductase thymidylate and synthase thymidylate gene (Trr1) thioredoxin reductase gene synthase and thymidylate gene (Trr1) (TS) gene synthase 36%; (TS) ⌘ 36%;= ⌘ gene (TS) 36%; and thymidylate = Null sequence Null divergence, sequence divergenc synthase gene (TS) 36%; ⌘ = no e synthase Trr1) gene (TS) 36%; and thymidylate ⌘= synthase Nullsequence =gene Null sequence (TS) ⌘divergence, = Nullnot 36%;divergence, not included included sequence in further in study divergence,studynotfurther for forITS genotyping; genotyping; included in no ˆITS study no ITS noamplification; ◎ = 78% ^ = for genotyping; = amplification; amplification; further ◎ == 78% SOD, 78% ITS^no =96.4% SOD, SOD, mt26S 96.4% 96.4% mt26S amplification; and mt26S ◎82.1% and and =82.1% 78% CYB; 82.1% CYB; SOD, ◉96.4% CYB;= 17/17 = ◉ =mt26S 17/17 mt26S 17/17 mt26S and and and mt26S CYB, and CYB, 82.1% 5/17 5/17 CYB, CYB; ◉SOD. SOD. 5/17 Country SOD. = 17/17 Country mt26S codes are a andcodes CYB, B; ◉ = 17/17 mt26S and Country CYB, 5/17 codes SOD. are according Country to ISO codes 3166-1 are alpha-3. according to ISO 3166-1 mt26S and 82.1% CYB; ◉ = 17/17 mt26S and CYB, 5/17 SOD. Country codes are according to ISO 3166-1 alpha-3. alpha-3. J. Fungi 2020, 6, 259 7 of 20 The aim of this study was to establish a consensus MLST scheme for P. jirovecii, taking into account the previously applied loci, to be used globally for P. jirovecii strain typing. Having a global consensus MLST scheme will allow for data exchangeability and comparisons of clinical isolates between laboratories, and the creation of an online world-wide MLST databank for P. jirovecii isolates. 2. Investigated Loci and Typing Schemes To select the most appropriate genetic loci all published loci and respective P. jirovecii genotyping schemes have been evaluated. Since 1994 nineteen genetic loci, representing either single or multi-locus genes, have been used in diverse genotyping analyses of P. jirovecii (see Table 1). Due to the limited DNA amount extracted from Pneumocystis positive clinical samples, the loci were rated based on their previous published amplification and sequencing success rates, as well as the diversity revealed per locus and subsequent ability to discriminate between strains. 2.1. Nuclear rRNA Gene Cluster Firstly, the multi-copy nuclear rRNA gene cluster was studied. It consists of five components which have been amplified and sequenced previously, including the 18S rDNA gene, the ITS1 region, the 5.8S rDNA gene, the ITS2 region and the 26S rDNA gene [6]. While the rDNA genes are highly conserved, the ITS regions show substantial diversity and as such have been used heavily for identification and genotyping of fungi [12]. The ITS1 and ITS2 regions have demonstrated the highest sequence variation among all loci of the rDNA gene cluster, as evident when sequenced as separate loci or in combination of the two regions (including the 5.8S gene), using nested-PCR techniques [3]. This has resulted in over 120 unique genotypes for both ITS regions reported and submitted to GenBank [74]. The ITS1 and ITS2 regions were chosen over the other genes in the rDNA gene cluster due to their superior discriminative power. 2.2. Mitochondrial Genes The mitochondrial large ribosomal subunit (mt26S) gene is involved in basic metabolic functions, with 15 copies within the genome [75]. This locus was selected as it has been considered to be a highly informative genetic marker due to its high variability between isolates, as well as being used as the main target world-wide for P. jirovecii detection and identification [76]. Another mitochondrial gene also selected was the cytochrome b gene, which contains approximately six copies per genome [75]. Cytochrome b oxidase gene (CYB) has been used widely within MLST genotyping of PCP infections and is increasingly commonly used within European hospitals and laboratories [41]. It has a reported high amplifying and sequencing success rate, although it offers a slightly lower variability than the mt26S locus. Although the mitochondrial small subunit (mtSSU) rDNA gene has over twice as many copies than mt26S gene, it has considerably reported lower variation over the mt26S gene, five unique genotypes compared to 25 [75,77]. Additionally, the locus has only appeared in six publications since 1998, when it was first sequenced for use in MLST. For all those reasons the mtSSU locus was not further considered for the consensus scheme. 2.3. Nuclear Genes Finally, three nuclear genes, β-tubulin (β-TUB), dihydropteroate synthase (DHPS) and superoxide dismutase (SOD) were also selected to be included in the study. β-TUB, is a single copy gene belonging to the tubulin coding gene family, which has been used for Pneumocystis identification and genotyping since the 19900 s and has been published within MLST schemes over 50 times [78]. Additionally, β-TUB has been used as a target locus for PCP diagnosis and is also part of the International Society of Human and Animal Mycology (ISHAM) MLST database (available online http://mlst.mycologylab.org), the only current MLST database specific to Pneumocystis, hence warranted further investigation [79]. SOD is a single copy gene encoding the production of the enzyme superoxide dismutase, which is commonly used in European studies as an efficient and discriminatory locus for genotyping [29,41]. J. Fungi 2020, 6, 259 8 of 20 SOD has a lower variation than β-TUB, but several studies have shown that these loci can be used to differentiate between colonised Pneumocystis (low burden levels) cases and high burden levels, such as in active PCP cases [80]. The final gene selected to be further investigated was DHPS, a highly studied locus due to nonsynonymous, point mutations within codons 55 and 57. These point mutations offer insights to trimethoprim-sulfamethoxazole (TMP-SMZ) resistance, due to the SMZ region of TMP-SMZ [81]. Drug resistances in P. jirovecii have been suggested by tracking the variations in DHPS, signifying an association between mutations and failure of prophylaxis with sulfa drugs [82]. Due to its high amplification success, along with the ability to give insight to resistance [70], DHPS is a key genetic region for many MLST studies. Despite its extensive use, low levels of genetic variation have been reported, with most studies reporting wild-type sequences being detected [83]. DHPS is also commonly genotyped together with DHFR, the dihydrofolate reductase encoding gene, as both enzymes are part of the folic acid pathway [46]. DHFR is inhibited by trimethoprim, nevertheless, information regarding the occurrence of mutations in DHFR are scarce, and also conflicting [70,82]. Studies have reported varying levels of DHFR mutations, from 2% to 60%, with no significant trends within global distributions, limiting its validity to be used for discrimination between samples [16,24,47,84]. Although this locus is still investigated within PCP treatment research, among the literature it shows slightly lower rates of variation than DHPS, and so would not add any further information when used alongside DHPS within a newly proposed MLST scheme. The major surface glycoprotein (msg) gene, upstream conserved sequences (USC) genetic regions of the kexin-like serine protease gene (Kex1), thymidylate synthase gene (TS), thioredoxin reductase gene (Trr1), as well as the 5-enolpyruvylshikimate-3 phosphate synthase activity (EPSP) region within the arom gene were not selected for further analysis within this study. These genetic regions displayed an inability to be adequately sequenced, as seen with the msg and USC genes [46,85]. The Trr1, TS, Kex1 and arom gene loci showed a minimal sequence divergence due to being highly conserved housekeeping genes, and, as such, they are not suitable for MLST, as their discriminatory power is too low [13,41]. As a result of this theoretical analysis the following seven genetic loci have been selected for further practical exploration in this study: β-tubulin gene, cytochrome b oxidase gene, dihydropteroate synthase gene, internal transcribed spacer 1 (ITS1), internal transcribed spacer 2 (ITS2), mitochondrial large ribosomal subunit rRNA gene (mt26S, also known as LSU-mt26S) and superoxide dismutase gene. 3. Amplification Rate and Variation of Target Loci Two cohorts of positive Pneumocystis DNA samples were independently subjected to amplification of the selected loci. The first cohort contained 44 bronchoalveolar lavage (BAL) samples which were PCP positive and were obtained from patients within Chilean hospitals between 2004 and 2014. The second cohort was composed of 23 oropharyngeal washes (OW) and 63 BAL samples from a single centre in Spain, between 2014 and 2018, with 35 positive PCP cases and 51 colonisations. P. jirovecii PCP was diagnosed either by Grocott-Gomori’s methenamine silver stain or direct immunofluorescence (Meridian Bioscience, Inc.) [86]. Samples were processed inside a biosafety cabinet using sterile precautions to avoid contamination. They were homogenised with a sterile pipette and a 200 µL aliquot was used for DNA extraction with the QIAamp® DNA Blood Mini kit (Qiagen). P. jirovecii was confirmed via PCR of the mitochondrial large subunit rRNA using the primers pAZ102-E and pAZ102-H [87]. Negative controls were included to monitor for cross-contamination during DNA extraction and purification. An internal control using the human β-globin gene [79] was used in each sample to detect false negatives. Each sample was run undiluted and as a 1/5 dilution. The samples were subjected to amplification to assess the effectiveness of the loci in a practical setting, within a range of Pneumocystis samples. To yield higher success rates the PCR primers and the associated amplification protocols were optimised from previously published conditions. Genes were amplified in volumes of 25 µL per PCR reaction, using 10X buffer (100 mM Tris-HCL, pH 8.3, 500 mM KCl, 15 mM MgCl2 and 0.01% w/v gelatine), 50 nM MgCl2 , 2 mM dNTPs, 10 ng/µL of each primer, J. Fungi 2020, 6, 259 9 of 20 5 U/µL BIOTAQ DNA (Bioline) polymerase and 10 µL of genomic DNA. The optimised primers and amplification conditions suggested to be used for the new consensus MLST scheme are shown in Table 2. The amplification conditions which have been used to amplify the loci not included in the new consensus MLST scheme are shown in the Supplementary Table S1. Table 2. Primer information for the loci of the novel MLST scheme. Product Size PCR Locus Primer Name Ref. Nucleotide Sequence (Base Pairs) Conditions PneumoβTub_F 50 -TCATTAGGTGGTGGAACGGG-30 95 ◦ C 3 min; β-TUB - 303 45 cycles: PneumoβTub_R 50 -ATCACCATATCCTGGATCCG-30 94 ◦ C 30 s, MnSODFw 50 -GGGTTTAATTAGTCTTTTTAGGCAC-30 60 ◦ C 45 s, SOD 5 602 72 ◦ C 45 s; MnSODRw 50 -CATGTTCCCACGCATCCTAT-30 72 ◦ C 7 min CytbFw 50 -CCCAGAATTCTCGTTTGGTCTATT-30 95 ◦ C 3 min; CYB 5 579 45 cycles: CytbRw 50 -AAGAGGTCTAAAAGCAGAACCTCAA-30 94 ◦ C 30 s, PneumoLSU_F 50 -TCAGGTCGAACTGGTGTACG-30 55 ◦ C 45 s, mt26S - 297 72 ◦ C 45 s; PneumoLSU_R 50 -TGTTCCAAGCCCACTTCTT-30 72 ◦ C 7 min Bidirectional sequencing was performed at Macrogen Inc., Seoul, South Korea. The obtained sequences where then assembled and edited using the software package Sequencher ver. 5.4.6 (Gene Codes Corporation). The cleaned-up sequences for each locus were aligned with the program CLUSTALW [88] part of the software MEGA version 10.1 [89] and compared to reference sequences listed in Table 2 and Supplementary Table S1. Allele types were named with respect to previously the published nomenclature [5,41]. The obtained amplification and sequencing success rates varied widely, with the nested PCR of the ITS1/2 locus being the lowest, with 2% for the Chilean isolates and only 38% of the Spanish isolates. DHPS and mt26S loci had the highest, which amplified 83% for the Spanish and 100% for the Chilean isolates and 95% of the Spanish and 100% of the Chilean isolates, respectively. Simple PCR of the ITS1 region with the newly designed primers amplified 47% of the Chilean isolates, although the Spanish were not amplified with this primer. This was then followed by the β-TUB locus, which amplified 80% of the Spanish and 78% of the Chilean isolates, the SOD locus, which amplified 71% of the Spanish and 91% of the Chilean isolates, and the CYB locus, which amplified 94% and 93% of both Spanish and Chilean isolates, respectively. Average amplification rates of the two cohorts are seen in Figure 1. The Fisher exact test statistic value indicated no significant differences between the individual cohort amplification rates for β-TUB, CYB and mt26S, and a significant result at p < 0.05 using the Fisher’s exact test [90] for the DHPS, SOD and ITS1/2 loci (for all raw data see Supplementary Table S2). The genetic loci were then assessed for their ability to discriminate between different strains, as a high variability within individual loci will directly increase the discriminatory value of the consensus scheme. Based on the PCR performance the ITS1/2 and ITS1 loci were not further analysed due to their poor amplification rates. The mitochondrial genes, mt26S and CYB, were found to have the highest variation, followed by β-TUB and SOD, as judged from the number of unique allele types obtained. The DHPS locus showed the least amount of variation, with the vast majority of alleles corresponding to the wild type and only two variants having been found across the entire collection of samples (Figure 2). A new database of all allele and sequence types has been established at http://mlst.mycologylab.org for the newly proposed consensus P. jirovecii MLST scheme. amplified 71% of the Spanish and 91% of the Chilean isolates, and the CYB locus, which amplified 94% and 93% of both Spanish and Chilean isolates, respectively. Average amplification rates of the two cohorts are seen in Figure 1. The Fisher exact test statistic value indicated no significant differences between the individual cohort amplification rates for β-TUB, CYB and mt26S, and a J.significant 259 at p < 0.05 using the Fisher’s exact test [90] for the DHPS, SOD and ITS1/2 loci10(for Fungi 2020, 6,result of 20 all raw data see Supplementary Table S2). Figure 1. Figure 1. Average Average amplification amplification and and sequencing sequencing rates rates for for all all targeted targetedgenetic geneticloci. loci.Calculations Calculationsare are based on the combined mean amplification and sequencing rates of both cohorts based on the combined mean amplification and sequencing rates of both cohorts and are and areexpressed expressedas as2020, J. Fungi percentages. 6, x FOR ErrorREVIEW PEER bars indicate the standard deviation. 8 of 17 percentages. Error bars indicate the standard deviation. The genetic loci were then assessed for their ability to discriminate between different strains, as a high variability within individual loci will directly increase the discriminatory value of the consensus scheme. Based on the PCR performance the ITS1/2 and ITS1 loci were not further analysed due to their poor amplification rates. The mitochondrial genes, mt26S and CYB, were found to have the highest variation, followed by β-TUB and SOD, as judged from the number of unique allele types obtained. The DHPS locus showed the least amount of variation, with the vast majority of alleles corresponding to the wild type and only two variants having been found across the entire collection of samples (Figure 2). A new database of all allele and sequence types has been established at http://mlst.mycologylab.org for the newly proposed consensus P. jirovecii MLST scheme. Figure 2. Figure 2. Number Number of of allele alleletypes typesidentified identifiedamongst amongstall allstudied studiedisolates. isolates. Based on Based onthe theabove aboveresults, results,showing showinga superior a superior amplification amplification rate rate andand sequence sequence quality, quality, andand high high discriminatory discriminatory power,power, the following the following four four loci: β-TUB, loci: β-TUB, CYB, and CYB, mt26S mt26S SODand SOD were were for chosen chosen for inclusion inclusion in in the proposed the proposed new consensus P. jiroveciiP. new consensus jirovecii MLST MLST scheme. scheme. 4. Case 4. Case Study: Study: Assessing Assessing the the Ability Abilityto toDiscriminate Discriminatebetween betweenClinical ClinicalIsolates Isolates To access To access the the efficiency to identify identify related related and and toto differentiate differentiatebetween unrelatedP.P.jirovecii betweenunrelated jirovecii isolates isolates these four loci were then used to genotype six positive Pneumocystis samples representing a four loci were then used to genotype six positive Pneumocystis samples representing apotential potentialcluster (two cluster epidemiologically (two linked epidemiologically isolates) linked and four isolates) andindependent cases. Allelic four independent cases.profiles Allelic were assigned profiles to eachto sample were assigned usingusing each sample the newly developed the newly developedMLST MLSTdatabase available database availableonline onlineatat http.mlst.mycologylab.org (Table 3) confirming the suspected to be related isolates and successfully separated all four suspected unrelated isolates (Figure 3). The two suspected related isolates showed identical MLST profiles corresponding both to the ST21. The four suspected unrelated isolates had all unique MLST profiles, ST2, ST7, ST42 and ST44, and where also different from the two related isolates (Table 1 and Figure 3). Cross contamination between samples was ruled out as samples were J. Fungi 2020, 6, 259 11 of 20 http://mlst.mycologylab.org (Table 3) confirming the suspected to be related isolates and successfully separated all four suspected unrelated isolates (Figure 3). The two suspected related isolates showed identical MLST profiles corresponding both to the ST21. The four suspected unrelated isolates had all unique MLST profiles, ST2, ST7, ST42 and ST44, and where also different from the two related isolates (Table 1 and Figure 3). Cross contamination between samples was ruled out as samples were analysed on different days and results were checked by resequencing a second aliquot. Table 3. Allele types and sequence types of two related and four unrelated P. jirovecii isolates. Colours indicate the different allele types per genetic locus. Strain Country of Date of Sequence β-TUB CYB mt26S SOD Number Origin Sample Type HVH21 Spain Jan 2015 2 1 3 1 ST21 HVH22 Spain Jan 2015 2 1 3 1 ST21 Case 63 Australia Dec 2016 1 3 1 4 ST42 Case 71 New Zealand May 2017 4 2 2 4 ST44 1794 Chile Feb 2011 2 5 4 1 ST7 2165 Chile Oct 2014 2 2 4 5 ST2 J. Fungi 2020, 6, x FOR PEER REVIEW 9 of 17 Figure 3. Figure 3. Phylogenetic Phylogenetic tree tree of six P. of six jirovecii isolates P. jirovecii isolates (patients (patients from from Table Table 3) 3) used used in in the the case case study study to to show the show thediscriminatory discriminatory power power of new of the the consensus new consensus P. jirovecii P. jirovecii MLST obtained MLST scheme, scheme, byobtained maximum by maximum analysis likelihood likelihood analysis with with the the general timegeneral time reversible reversible (GTR) model (GTR) model with with RaxML RaxML (version(version 7.2.8) 7.2.8) using using RaxmlGUI RaxmlGUI 1.1 part 1.1 [91], part [91], of theofsoftware the software package package MEGA MEGA ver.[92]. ver. 7.0 7.0 [92]. 5. Discussion 5. Discussion Genotyping ofofP. jirovecii Genotyping is vital P. jirovecii is for thefor vital advancement of understanding the advancement of the biology, of understanding of pathogenesis, the biology, epidemiology, prophylaxis and treatment regimen of this human pathogen, but more pathogenesis, epidemiology, prophylaxis and treatment regimen of this human pathogen, but more specifically it is vital to help itmanage, specifically is vitalcontain to helpand preventcontain manage, nosocomial clusters. nosocomial and prevent With a rise of nosocomial clusters. Withoutbreaks a rise of since the early 2000s, hospitals have recorded catastrophic consequences of PCP nosocomial outbreaks since the early 2000’s, hospitals have recorded catastrophic consequencesoutbreaks, with upof to 83% of reported outbreaks being described within organ transplant wards, PCP outbreaks, with up to 83% of reported outbreaks being described within organ transplantas well as in patients with wards,haematological malignancies as well as in patients and connectivemalignancies with haematological tissue diseases [93]. and Large graft connective failure tissue and over diseases [93]. Large graft failure and over 50% casualties in wards has been reported from single outbreaks, demonstrating the severity of this underestimated disease [94]. An effective way to investigate epidemiological links is through the creation of transmission maps by combining molecular typing along with studying patient encounters and interactions within the hospital [5]. However, the fact that there are currently 19 genetic regions being used in 31 J. Fungi 2020, 6, 259 12 of 20 50% casualties in wards has been reported from single outbreaks, demonstrating the severity of this underestimated disease [94]. An effective way to investigate epidemiological links is through the creation of transmission maps by combining molecular typing along with studying patient encounters and interactions within the hospital [5]. However, the fact that there are currently 19 genetic regions being used in 31 different typing schemes for P. jirovecii limits effective epidemiological studies. The lack of a consensus scheme directly inhibits the ability to compare results, polymorphic strains, and epidemiological data between research centres, and hinders the possibility of establishing global databases and conducting large-scale population studies. To overcome these limitations, a comprehensive study of all genes and schemes was herein undertaken to assess which loci and which combination of loci would allow for the development of the most practical, efficient and discriminatory scheme. Previous studies looked at the performance of various schemes to suggest a possible consensus scheme, but none have since been formally brought forward as a suggested universal scheme [3]. Maitte et al. 2013 [5], in their review suggested that an eight loci scheme provided the most powerful genotyping results, but this is only possible theoretically due to the limited amount of DNA available from P. jirovecii in clinical samples. There are no reliable methods to culture the P. jirovecii in vitro, therefore the DNA amount which comes directly from clinical samples is limited [7]. The volume is then further limited depending on the fungal load as well as the source of the specimen [95]. HIV positive patients have high fungal loads, whilst colonised carriers and HIV-negative PCP patients carry lower levels [96]. Bronchoalveolar lavage specimens are the preferred sample, yielding the highest sensitivity due to a greater fungal concentration and also yielding an acceptable negative predictive value [97]. The same studies have shown that the less invasive method, induced sputum (IS), showed comparable levels of fungal burden as BAL, followed by oropharyngeal washes, and then to a lesser extent nasopharyngeal aspirates, and nasal swabs [93,95]. It is therefore vital to have a typing system, consisting of as few genetic loci as possible, but being able to detect and amplify specimens with low levels of fungal burden, as this is often the first limiting step when undergoing Pneumocystis genotyping analysis. On the other side, having too few loci also poses a problem, since lowering the number of loci in a scheme then decreases the discriminatory power and the ability to distinguish between closely related strains. Studies have shown that often schemes with less than three loci do not have enough variation to accurately genotype, as such the Hunter (H)-index has been used in multiple studies to demonstrate the discriminatory power of a scheme [5]. The H-index should not be the only determining factor of an effective scheme as it is highly variable depending on the number of isolates being tested, but it has been a useful tool to help predict the estimated discriminatory power of a scheme [98]. A H-index of 0.95 or higher is considered a suitable cut-off benchmark for MLST schemes, and the review by Maitte et al. 2013 [5] showed that there were no genetic regions which could work individually or paired with another, that would meet this cut-off [19]. As seen in Table 1, there are multiple schemes used in genotyping which are comprised of only two loci, casting a shadow of doubt on their results and generated epidemiological data of these studies, further reinforcing the need for standardisation amongst the Pneumocystis scientific community. As a result, eight genetic regions were explored in this study as potential loci which could be included in a global consensus scheme, by analysing their amplification ability and demonstrating their discriminatory power. The whole ITS region is widely reported to have the most variability within P. jirovecii and is highly useful when identifying and genotyping other invasive fungi [74]. Unfortunately, it also has been reported to have a high amplification failure when applied to P. jirovecii [59], which was also evident in the current study, as ITS1 alone and ITS1/2 regions showed to have the lowest amplification capability, unable to amplify and successfully sequence more than 50% of the studied isolates for either primer set. Studies have reported that using nested-PCR instead of conventional, single-round PCR can help to overcome the lack of amplification for the ITS region [3,99]. This was not the case in the herein reported study, as the nested-PCR protocol for the ITS1/2 regions performed J. Fungi 2020, 6, 259 13 of 20 considerably worse than single round PCR for the ITS1 region within the Chilean cohort. Due to the lack in amplification success, both in this study and others, no loci from the nuclear rRNA gene cluster were further considered for involvement in a new consensus MLST scheme. Conversely to the ITS region, DHPS amplification was highly successful achieving a global 91.5% amplification success, with minor variations that can be attributed to differences associated to the spectrum of clinical settings covered, ranging from colonisations to infections. DHPS is heavily used among P. jirovecii genotyping and has been consistently used since the late 1990s in diverse schemes. Despite this, within the reported literature, DHPS does not reveal much variation, as such most often wild-types are reported, carrying no informative data to discriminate between strains, showing a H-index of 0 in previous studies [5,100,101]. DHPS has demonstrated effectiveness when exploring TMP-SMZ resistance, by showing mutations at the 55 and 57 codons [102]. Population studies using the DHPS locus have effectively been able to track additional sulfa pressure in geographical regions with or without widespread use, and as such accurately predict or identify sulfamethoxazole resistance within these regions [103,104]. In this study, only two allele types have been identified, with most of the isolates showing the wildtype, showing regional differences in the distribution of wildtype and allelic variants, subject to further studies. The mutations can be used to give an insight in the widespread use of TMP-SMZ, and for a further comparison between other geographical locations heavily using SMZ but not showing resistance within the community. From a genotyping perspective, the DHPS locus, however, does not offer enough variation to be considered as a useful locus within a consensus scheme, and was therefore no longer considered within this study. Despite its drawback to sufficiently discriminate between isolates, researchers should maintain DHPS typing for assessing prophylaxis and treatment resistance within populations, and DHPS can further be explored for its use as an identifying genetic target in PCP diagnosis due to its successful amplification properties. Two schemes which use the loci explored in this study and are predominant in the literature are: The official scheme promoted by ISHAM [3], consisting of β-TUB, DHPS, ITS1 or ITS1/2 and mt26S; and a French scheme first proposed by Maitte et al. 2013 [5], consisting of CYB, mt26S and SOD. The ISHAM scheme is highly discriminatory, when applied to both herein studied cohorts it resulted in an H index of >0.98. for both cohorts. The H index was calculated as per Hunder et al. 1988 [98]. Due to different ITS regions explored, ITS1 in the Chilean cohort was able to identify 23 unique sequence types using this scheme, and ITS1/2 in the Spanish cohort attained 14 sequence types. The Maitte et al. 2013 [5] scheme has been reported to have a H-index above 0.95, but this index fell below the threshold when larger sample sizes were considered. H indexes ≤ 0.945 were attained when herein applied to the Chilean and Spanish cohorts, with 33 unique ST detected. Since the DHPS and ITS are not appropriate loci to be used in MLST schemes, the ISHAM scheme could not be promoted for universal application, and neither could the Maitte et al. 2013 [5] scheme, due to inconsistencies with sub-optimal levels of discrimination. β-TUB, CYB, mt26S and SOD genetic regions were all individually effective in amplification, but unable to individually discriminate effectively enough, therefore a new consensus MLST scheme comprising of these four loci is herein proposed. When applied to both cohorts, the new MLST scheme was able to discover a total of 38 unique sequence types, with a combined H-index of 0.975, which is well above the discriminatory cut-off margin for any useful MLST typing scheme. As this new MLST scheme had not been previously used, the next step was to explore the effectiveness of the scheme to successfully individual P. jirovecii isolates. The new MLST scheme was applied to two suspected epidemiologically linked isolates and four isolates for which clinical metadata suggested no relationship, to determine whether it would be discriminatory enough to distinguish the isolates appropriately. The MLST analysis revealed a distinct cluster, showing the genotype ST1, consisting of two patients, named HVH21 and HVH22. The identical sequences of patient HVH21 and HVH22 confirmed the suspected fact of relatedness, which is based on the metadata of the patients, which suggested a possible nosocomial cross-transmission. The cluster involved an HIV positive J. Fungi 2020, 6, 259 14 of 20 colonised patient and a colonised lung transplant recipient, both with a positive BAL, obtained three days apart. Transmission could have taken place at the radiology department, which both had attended on the same day. The other four epidemiologically unlinked isolates were successfully separated from the cluster and revealed each a unique sequence type, ST7, ST13, SR18 and ST21, which was expected as they were obtained from patients from different geographic regions, including Australia, New Zealand and Chile. With the Chilean isolates originating from patients from different Chilean health centres (public and private) three years apart. As such, the newly established consensus MLST scheme has demonstrated its ability to discriminate appropriately between P. jirovecii isolates, making it a powerful tool to identify identical strains in settings with many associated cases, such as in an outbreak situation. However, the obtained typing data should always be complemented with a clinical history as good as possible to trace back the origin. The herein obtained results demonstrated that the new MLST scheme consisting of β-TUB, CYB, mt26S and SOD (Table 2) has a much higher amplification rate and an efficient discriminatory power to be applied for genotyping of P. jirovecii isolates from clinical samples with high and low fungal burdens, including disease causing and colonising isolates. Promoting this novel MLST scheme as a global consensus scheme will for the first time standardise MLST for the human pathogen P. jirovecii and set up the basis of a substantial improvement in understanding the relationship between clinical P. jirovecii isolates. This will allow real-time genotyping of current infected patients and suspected colonised carriers to be now undertaken to improve the understanding of transmissions and the effect colonised carriers have on nosocomial spreads. Further, this will influence public health approaches for preventing nosocomial infections, in especially high-risk patients, such as those recovering from organ transplantation in close approximate in hospital wards. Since there is no current database, outside of the ISHAM MLST database [3], available online at http://mlst.mycologylab.org/, it is difficult to find all currently published allele types and the lack of standardisation across global centres often cause confusion, even when attempting to compare allele types of a certain locus. The new global database, also placed at http://mlst.mycologylab.org, established herein will improve the nomenclature of allele types and sequence types and makes it easier for researchers and clinician to have one source of information for all genotyping data. The herein standardised MLST scheme will enable the establishment of such a global database, which can be used by all clinical diagnostic and research centres to deposit metadata and sequences, allowing to compare global specimens, something which was not previously possible. 6. Conclusions In conclusion, this study demonstrates the importance of a consensus MLST scheme for P. jirovecii genotyping and the formation of a global database in expanding the understanding of this important human pathogenic fungus. Based on the previous schemes and the evidence in this study, a novel MLST for the genotyping of P. jirovecii, consisting of four genetic regions: β-TUB, CYB, mt26S and SOD is proposed. This combination of loci maximises the likelihood for amplification and adequate discrimination of isolates over previously used schemes and will aid hospitals in drawing conclusions about interhuman transmission between patients, and hopefully minimise or early detect nosocomial outbreaks. Supplementary Materials: The following are available online at http://www.mdpi.com/2309-608X/6/4/259/s1, Table S1: Primer information for the initially tested but finally not selected loci. Table S2: Amplification rates of all tested loci for both cohorts. Author Contributions: Conceptualization, W.M. and M.T.M.-G.; methodology, L.P., L.G., L.I. and C.A.P.; validation, L.P. and L.G.; formal analysis, L.P., L.G., and M.G.-M.; investigation, L.P. and L.G.; resources, W.M. and M.T.M.-G.; data curation, L.P., L.G. and A.K.; writing—original draft preparation, L.P., L.G., M.T.M.-G. and W.M.; writing—review and editing, L.P., L.G., M.G.-M., L.I., A.K., C.A.P., S.L.V., M.T.M.-G. and W.M.; visualization, L.P.; supervision, W.M. and M.T.M.-G.; project administration, W.M.; funding acquisition, W.M., S.L.V. and M.T.M.-G. All authors have read and agreed to the published version of the manuscript. J. Fungi 2020, 6, 259 15 of 20 Funding: This study was supported by a National Health and Medical Research Council of Australia (NH&MRC) grant [no. APP1121936] to W.M., by a National Fund for Science and Technology from Chile (Fondecyt-ANID) grant [no. 1140412] to S.L.V. Acknowledgments: The authors thank all clinicians and clinical microbiologists who submitted clinical samples to the study. Conflicts of Interest: The authors declare no conflict of interest. References 1. Meenakshi, K.; Gowtham, R.R.; Usha, K. Pneumocystis jirovecii Pneumonia: A Revisit to the Old Malady. J. Clin. Diagn. Res. 2019, 13, DE01–DE08. [CrossRef] 2. Morris, A.; Lundgren, J.D.; Masur, H.; Walzer, P.D.; Hanson, D.L.; Frederick, T.; Huang, L.; Beard, C.B.; Kaplan, J.E. Current epidemiology of Pneumocystis pneumonia. Emerg. Infect. Dis. 2004, 10, 1713–1720. [CrossRef] [PubMed] 3. Phipps, L.M.; Chen, S.C.-A.; Kable, K.; Halliday, C.L.; Firacative, C.; Meyer, W.; Wong, G.; Nankivell, B.J. 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