Specific protease mutation patterns are associated …446 Specific protease mutation patterns are associated with oropharyngeal candidiasis in a New Orleans patient cohort of HIV-infected

446

Specific protease mutation patternsare associated with oropharyngealcandidiasis in a New Orleans patientcohort of HIV-infected individuals

Peter J. Hickman1

Robertino M. Mera2

Janet E. Leigh1,3

Paul L. Fidel Jr.1

Allen R. Mock1

William R. Gallaher1

Ronald B. Luftig1

1Department of Microbiology, Immunology and

Parasitology2Department of Pathology3Department of General Dentistry

Louisiana State University Health Sciences Center

Received for publication: January 31, 2004Accepted: March 22, 2004

Correspondence to:Ronald B. LuftigLouisiana State University Health Sciences Center1901 Perdido StreetNew Orleans, LA 70112-1393Phone: (504)568-4063Fax: (504)568-2918e-mail: [email protected]

Abstract

HIV-1 protease gene sequences were obtained from peripheral blood,

saliva or oral tissues of 35 HIV+ patients using nested amplification

and manual sequencing of PCR products. Of the 35 HIV+ patients 9

had clinical oropharyngeal candidiasis (OPC) while 26 did not, and

only 4 patients were on protease inhibitor (PI) therapy. These pa-

tients were collected prior to major use of HAART therapy in New

Orleans, Louisiana. Analysis of 172 amino acid sequences revealed

unique patterns of mutation that were in most cases independent of

the type of cell from which DNA was isolated and were, instead,

primarily dependent on the individual patient. Principal component

analysis indicated that approximately 50% of the variance of the amino

acid replacements could be explained by patterns of change seen in

only five patients. Significantly, 4 of these 5 patients were OPC+

indicating that patients with OPC are more likely to express a princi-

pal mutation pattern than patients without OPC (p = 0.002, Chi

square). Dendrograms revealed that these five patients clustered sepa-

rately from each other and from HIV-1LAI

suggesting that principal

mutation patterns as well as OPC are independent of viral evolution.

In conclusion, prior to widespread use of PI therapy to combat HIV-1,

patients with OPC exhibited unique patterns of amino acid replace-

ments within the HIV-1 protease.

Key Words:

HIV-1, mutation, proteases, candidiasis

Braz J Oral Sci. April/June 2004 - Vol. 3 - Number 9

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Braz J Oral Sci.3(9):446-453 Specific protease mutation patterns are associated with oropharyngeal candidiasis in a New Orleans patient cohort of HIV-infected individuals

IntroductionOne of the key areas of concern for infected patients is themaintenance of a persistent HIV-1 infection in the presence ofan active immune response. This is in part due to reservoirsof HIV-1 infection1 wherein the virus is protected from notonly host defenses but also from highly active antiretroviraltherapy (HAART) (see review by Ogden and Flexner2, 2001).In these sites, the virus or its proviral genome can remain in alatent or persistent state where it can undergo mutationalchanges in a prolonged infection. Examples of such sites arethe oral cavity despite the presence of secretory leukocyteprotease inhibitor (SLPI)3, inducible lymphoid sites duringHAART4 and quiescent T cells that can be activated withprostatin5. The presence of virus in such reservoirs isevidenced by the rapid rate of viral rebound once HAART orother antiviral therapy is removed6. Despite the relative deficitof virus in the oral cavity, oral lesions such as OPC(oropharyngeal candidiasis), hairy leukoplakia and periodontaldiseases (necrotizing gingivitis and periodontitis) as well ashuman papilloma viral warts have been associated with HIV-1infection7.The oral carriage rate of Candida sp. is high (60-70%), yet fewif any healthy individuals develop oropharyngeal candidiasis.In contrast, the majority of HIV-1 infected individuals, prior tothe widespread use of HAART, developed OPC7. This studyused programs from the Statistical Package for Social Sciences(SPSS) and the Phylogeny Inference Package (PHYLIP) toexamine the relationship of protease gene mutation patternsin a cohort of 35 HIV-1 infected individuals from New Orleans.Based on interviews of patients and examination of theirmedical records, most of the patients (89%) in this prospectivestudy were not taking protease inhibitors at the time tissuewas obtained. Although in 89% of the patients there is noevidence of medically accepted anti-HIV-1 therapy, we cannotrule out alternative medicines or other non-standard therapy.Surprisingly, in this study a high correlation was found withspecific mutation patterns in a subset of patients and thepresence of OPC. Of course, one cannot eliminate thepossibility of spontaneous mutations; however, one wouldthink this unlikely to the degree seen for such a highlyconserved gene (see Figure 4 legend).

Material and MethodsIsolation of template DNA, amplification, and purification andsequencing of PCR products. New Orleans patients wereenrolled in this study over a 21 month period only afterinformed consent, and procedures were performed in strictadherence to the guidelines of the Institutional Review Boardof the Louisiana State University Health Sciences Center. The35 patient cohort was obtained relatively early in the HIVdisease epidemic in New Orleans (between 9/30/96 and 6/30/98), and only 4 patients (=11.4% of the cohort) were beingtreated with protease inhibitors as part of HAART. Details on

the make-up of this pilot population (ethnicity, sex, age) weretaken into account during our statistical analysis and havestood out as confounders. Genomic DNA or cDNA wasisolated from peripheral blood mononuclear cells (PBMC orb), unstimulated saliva (s) or oral biopsy of gingival cuff (g),buccal mucosa (c), tongue (t) or palate (p) tissues as describedpreviously8. DNA samples were amplified using nested primersspecific for the HIV-1 protease as described previously8. PCRproducts of the predicted size were gel purified from extraneousbands and excess primers using the QIAquick Gel ExtractionKit (Qiagen, Valencia, CA, USA) according to manufacturer’sinstructions, and PCR products were directly sequenced usingthe Thermo Sequenase Radiolabeled Terminator CycleSequencing Kit (USB Corporation, Cleveland, OH, USA) asdescribed previously8.

Statistical analysis of cohort data. We initially chose toexamine the 172 protease sequences by principal componentanalysis using the Statistical Package for Social Sciences(SPSS) to see whether particular mutation patterns werecorrelated with source of DNA (genomic DNA versus cDNA),cell type from which the DNA originated (oral compartmentversus humoral/systemic) or individual patients. Principalcomponent analysis is a multi-dimensional method thatproduces a single unique solution from a correlation matrix.Initially, the analysis produces a crude table of variances (notunlike that seen in Table 1) and is followed by a VarimaxRotation of data and interpretation of the solution. Eachvariable will now have a certain loading value (between –1.0and 1.0) that describes the correlation between the individualvariables and the overall set of factors. The “most significant”scores are listed by factor and the Varimax Rotation results ina fairly even distribution of loading scores9. It is true that theuse of SPSS is normally limited by such a small sample size;however, because the experienced statistician on the study(Dr. Robertino Mera) was so impressed that the sum ofvariances of only five factors approached 50%, we decided toproceed with the analysis and report our results.All nucleotide sequences were translated into amino acidsequences using the universal genetic code and conventionalsingle-letter abbreviations for amino acids. A capital letterindicates that the only species present in the given PCRproduct is different from the HIV-1

LAI reference strain at that

position, whereas a small letter indicates a mixture of mutantprotease and HIV-1

LAI-like protease at the DNA level. When

microheterogeneity was observed two or three times within asingle codon, we assumed that all mutations were occurringsimultaneously. Amino acid substitutions were identified asstructurally/functionally conservative, nonconservative orradical replacements according to the system of Gallaher etal.10. In order to increase the signal to noise ratio in thesequence data, amino acid positions were selected for principalcomponent analysis by a three step process as follows: 1)

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accept only positions where 10% or more of the samples hada replacement; 2) add amino acid positions which by visualinspection appear to be sites of replacement for a particularpatient even though they may be rarely-occurring sites ofreplacement in the overall sample set; 3) perform a principalcomponent analysis and drop all positions that are non-loading(that is, not a component of the first ten factors).The use of PHYLIP programs to produce dendrograms issummarized as a flow diagram in Figure 1. For parsimonyanalysis, files representing nucleotide sequences weremanually adjusted to Pearson’s (FastA)11 sequential formatusing Microsoft Word 97, version SR-2 and Word Pads toproduce the text file infilen.txt. DNA and protein sequenceswere aligned via the CLUSTALW version 1.7 program usingthe IUB DNA weight matrix or the BLOSUM30 protein weightmatrix12. This produced the files “infilen.phy” or “infilep.phy”.Nucleotide sequences were translated manually using theuniversal genetic code and aligned by visual inspection.Protein sequences and alignments were verified using thednaSP program version 3.0 program to translate “infilen.phy”followed by alignment using the Advanced BLAST version2.0.8 program13.

Fig. 1- Flow Diagram of Sequence Analysis using PHYLIP Programs.

ResultsIn a more recent 2002 study involving a larger cohort of 80patients 71% of whom were undergoing antiretroviral,including HAART therapy, we noted that the protease geneencoded amino acid sequences that by visual inspection wereunique for each patient8. Furthermore, a “dtvpc” motif at theactive site occurred in 6.4% of the protease gene sequences,and a stop codon (“z”) was observed in 17.7% of the proteasegene sequences. We predict that both of these types ofmutation, if expressed, would inactivate the protease andpotentially lead to defective viral particles. These uniquefeatures are illustrated by the HIV-1 protease sequences ofthree patients shown in Figure 2. Note that by visualinspection of any given patient there is a high degree ofintrapatient similarity in the sequences derived from differentcell types, yet the consensus sequences of the three patientsin Figure 2 clearly show interpatient differences.SPSS factor analyses revealed unique patterns of amino acidmutations that were mostly dependent on individual patients.The pattern and number of mutations were independent ofsource of DNA (genomic DNA versus cDNA) and inapproximately 90% of the patients were independent of thecell type from which the DNA originated (PBMC, saliva ororal tissues). Cross tabulations of amino acid replacementswere performed on 172 sequences obtained from the 35 patientcohort, and the results are shown in Table 1. Six of the eightfactors can be attributed to mutation patterns within a smallsubset of patients. Specifically, five patients have beenidentified whose mutation patterns explain six of the factorsand account for 42.7% of the variance in the entire 35 patientdata set. Factor 2 (accounting for 7.1% of the variance) is thefrequently occurring “dtvpc” motif near the active site of theprotease, and factor 5 (accounting for 6.3% of the variance) isprobably the result of guanosine to adenosine mutation hotspots occurring at the only two tryptophan residues of theHIV-1 protease (leading to stop codons) and also occurringin the conserved glycine-rich region corresponding to theflap of the homodimer HIV-1 protease which allows (orprecludes) substrate binding.Cross tabulations of nonsynonymous replacements withineach factor were calculated by Chi-square analysis. The pvalues for these tests are shown in the last column of Table 1,and the low p values (< 0.05) indicate that thenonsynonymous amino acid mutations that loaded highestin the factor analysis were significant meaning that theyoccurred with a frequency higher than expected by chance.We observed that, despite a predominantly OPC- cohort,among the five patients whose amino acid mutation patternswere principal components of the SPSS analysis only patient24 was OPC-. Fisher statistical analysis was performed todetermine the relationship between OPC status or CD4+ cellconcentration and the five patients who demonstrate principalmutation patterns (see Table 2). Our data suggest that patients


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with OPC are significantly more likely to express a principalmutation pattern than patients without OPC (p = 0.01); incontrast, patients with fewer than 200 CD4+ cells/µl are nomore likely to express a principal mutation pattern thanpatients with more than 200 CD4+ cells/µl (p = 0.33). Theserelationships were verified by Chi square analysis where pvalues were 0.002 or 0.06, respectively, for OPC+ status orCD4+ cell concentration.Nucleotide sequences were analyzed by commonphylogenetic and polymorphic methodologies to examineby another technique the results of our SPSS statisticalanalysis. A key difference in these approaches is thatprincipal component analysis provides structuralrelationships among the patients while the PHYLIP programsare designed to reveal epidemiological relatedness amongthe patients, 80% of whom provided samples within the firstfive months of the study.In order to provide such an independent statistical approach,an examination of the 172 nucleotide sequences wereundertaken by PHYLIP analysis14. This involved performing

Fig. 2. Deduced Amino Acid Sequences of the HIV-1 Protease Amplified from Three of the Patients whose Amino Acid Mutation Patterns werePrincipal Components of the SPSS Analysis. At the top of the Figure is the LAI protease gene sequence, for comparison. Roman numerals I-Vrepresent highly conserved regions, such as the D-T-G amino acids 25-27 which are at the active site. Directly sequenced PCR products areshown for all three patients along with the consensus sequence of each patient. Single arrows represent no change in the majority of encodedamino acids (corresponding to a synonymous, or silent, nucleotide substitution), double arrows represent conservative amino acid replacements,* represent non-conservative replacements, and the letter z represents a radical change such as the introduction of a stop codon.

highly stringent multiple sequence alignments at thenucleotide level and included the HIV-1

LAI pattern (equivalent

to the consensus Los Alamos HIV-1 Group B sequence exceptfor an A to G substitution at position 110 of the pro gene) asthe outgroup15. Figure 3 shows the maximum parsimonyanalysis at the nucleotide level of the five patients thatrepresent the first eight factors shown in Table 1. There isclearly intrapatient clustering of sequences in thephylogenetic tree, a lack of interpatient similarity and a lackof sample site-specific clustering.Finally, based on the crystal structure of the HIV-1 proteasehomodimer, we were able to model the protein highlightingamino acid positions (Figure 4A) that demonstratednonsynonymous replacements or demonstrated noreplacements. As can be seen in Figure 4B, amino acidpositions that never changed tended to be at the active siteand at other points where the two subunits interact.Positions that could tolerate nonsynonymous replacements,in contrast, tended to be on the surface of the protein exposedto the aqueous environment (see Figure 4C).


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Table 1. Factors of the Principal Component Analysis and Cross Tabulation of Nonsynonymous Amino Acid Replacements.


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Table 2. Correlation of OPC Status or CD4+ Cell Concentrationwith Patient Mutation Pattern. Note in Table 2 at bottom:with asterisk by odds ratio (OR). Statisticians differ on whatpopulation size is needed for a significant OR.

Fig. 3. Maximum Parsimony Analysis at the Nucleotide Level of the Five Patients whose Amino Acid Mutation Patterns were PrincipalComponents of the SPSS Analysis. The five large numbers in bold refer to the patient identification number, and the combination of letters andnumbers by each line refer to individual sequences from a given patient. Individual sequences were named according to cell type from whichDNA was isolated, the form of DNA that was isolated and the date on which HIV-1 pro was selectively amplified (8). For example, in the upperleft corner of the figure is the branch corresponding to patient 25.

DiscussionAs noted earlier, the multivariate statistical approach ofprincipal component analysis is designed to analyze theprotease substitution patterns at the amino acid level andcondense data from the original variables into a small set offactors9. In this study, as seen in Table 1, principal componentanalysis revealed that 5 patients explained about 43% of thevariance and two additional factors showed significance aswell, one corresponding to a “dtvpc” motif and anothercorresponding to G to A hypermutations which have beendemonstrated to occur at a high rate in HIV-1 genes16.As we learn more about HIV-1 protease inhibitors, we arefinding that PI resistance2, co-infections with tuberculosis1,interactions with health foods6 and integration into quiescentT-cells4 are all mechanisms that allow persistence of HIV-1and eventually movement of proviral DNA into reservoirswhere virus can be activated at late stages of AIDS.In addition to learning more about the basic biology of theHIV-1 protease, this study provides an in-depth analysis ofthe changes in HIV-1 protease patterns that may be happeningin a remote location of the body, the oral cavity, where virus


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Fig. 4. HIV-1 Protease X-Ray Crystallographic Structure with Se-lected Amino Acid Positions Highlighted. Part A: Linear sequence ofthe HIV-1

LAI reference strain. Part B: 3-dimensional model of the 25

positions where no replacements were observed. Part C: 3-dimen-sional model of the 38 positions where non-synonymous replace-ments were observed.

can mutate while persisting associated with cells. Here externalfactors such as SLPI, the SLPI receptor, uncharacterized entitiesin saliva as well as Candida-specific secreted aspartylproteases (SAPs)17 may exert selection on the HIV-1 protease.HIV-1 sequences obtained from oral tissues weredistinguishable from those obtained from PBMC inapproximately 10% of the patients which is consistent with asmall but real variation in pro for the oral cavity8. Conversely,HIV-1 sequences obtained from oral tissues were identical tothose obtained from PBMC in approximately 90% of thepatients which may reflect contamination of oral tissues withblood or may indicate that the predominant oral virus hasmoved into the PBMC.Thus, when examining HIV-1 gene sequence variation, oralsites should be considered especially in OPC+ patients.Cytokine expression is different in the oral cavity, andcandidiasis may also exert a selective pressure in the presenceof protease inhibitors18 potentially leading to increasedproduction of variant proteins or defective particles that mightbe more lethal at advanced stages of disease19. There is alsoin vitro evidence using a murine model that C. albicansvariants with elevated levels of SAPs are more pathogenicthan isolates that produce low levels of SAPs20. We do notknow what selective pressure SAPs might have on the HIV-1protease. Since some antiretroviral PIs are known to crossreactwith some of the SAPs produced by C. albicans18, it is possible,for example, that high levels of SAPs might compete with HIV-

1 protease for PI binding and effectively protect the HIV-1protease from developing PI resistant mutations. On the otherhand, perhaps high levels of SAPs compete for viral precursorsubstrates and interfere with the maturation of viral particlesunless particular mutations in the HIV-1 protease emerge.Experiments will be performed where recombinant SAPs areadded to HIV-1

LAI-infected cells to see if specific mutations

arise in the HIV-1 protease.It is unclear whether OPC causes a higher mutation rate andunique mutations to arise in the HIV-1 protease or if specificmutations in the HIV-1 protease affects the immune system insuch a way that the patient is more susceptible to OPC infection.Regardless of cause and effect, there is clearly a relationshipbetween OPC and unique patterns of mutation in the HIV-1protease among patients where there is little selective pressureon the HIV-1 protease due to PI therapy. We are currentlyinvestigating the possibility that other oral infections such asoral hairy leukoplakia (OHL) or human papillomavirus (HPV)might interact with HIV-1 in a manner similar to OPC leading tohigh numbers or unique patterns of mutation in the HIV-1protease.Finally, Figure 4 shows that the mutations selected in HIV+

patients who have “not” been extensively treated with HAARToccur predominantly in regions outside of the highlystructurally conserved active site and flap. One cannot ruleout that the cluster effect seen for OPC represents transmissionfrom the same partner or intravenous transmission at the sameperiod. We also expect that as patients are increasingly treatedwith HAART we should see mutations at characteristic sitesof PI resistance.

AcknowledgmentsThis work was supported in part by NIH grant DE-12178awarded to Dr. Paul L. Fidel Jr. and institutional funds. Wewish to thank Stephen Strickland, Ryan Jackson and JenniferAbadie for their technical assistance as summer students inthe lab of Dr. Ronald B. Luftig. Especially, this work could nothave been performed without the extensive mentorshipprovided to Allen Mock by Dr. William Gallaher.

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Specific protease mutation patterns are associated …446 Specific protease mutation patterns are associated with oropharyngeal candidiasis in a New Orleans patient cohort of HIV-infected