antibody repertoires and pathogen recognition

157 Pages·2012·2.79 MB·English

MihaelaL.Oprea
Candidate
DepartmentofComputerScience
Department
Thisdissertationisapproved,anditisacceptableinquality
andformforpublicationonmicrofilm:
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Date
ANTIBODY REPERTOIRES AND PATHOGEN
RECOGNITION: THE ROLE OF GERMLINE
DIVERSITY AND SOMATIC HYPERMUTATION.
by
Mihaela L. Oprea
M.D.,UniversityofMedicineandPharmacy,Timisoara,Romania,1992
M.S.,ComputerScience,UniversityofNewMexico,Albuquerque,1996
Dissertation
SubmittedinPartialFulfillmentofthe
RequirementsfortheDegreeof
Doctor of Philosophy
Computer Science
TheUniversityofNewMexico
Albuquerque,NewMexico
May 1999
c 1999,MihaelaL.Oprea
iii
ANTIBODY REPERTOIRES AND PATHOGEN
RECOGNITION: THE ROLE OF GERMLINE
DIVERSITY AND SOMATIC HYPERMUTATION.
by
Mihaela L. Oprea
Abstract of Dissertation
SubmittedinPartialFulfillmentofthe
RequirementsfortheDegreeof
Doctor of Philosophy
Computer Science
TheUniversityofNewMexico
Albuquerque,NewMexico
May 1999
ANTIBODY REPERTOIRES AND PATHOGEN
RECOGNITION: THE ROLE OF GERMLINE
DIVERSITY AND SOMATIC HYPERMUTATION.
by
Mihaela L. Oprea
M.D.,UniversityofMedicineandPharmacy,Timisoara,Romania,1992
M.S.,ComputerScience, UniversityofNewMexico,Albuquerque,1996
Ph.D.,ComputerScience, UniversityofNewMexico,1999
Abstract
The classical view of the immune system is that it constructs its receptors so as
to recognize as many molecular shapes as possible. This mechanism is anticipatory in
the sense that no prior knowledge of the pathogens needs to go in the construction of the
immunereceptorsthatcanbindthesepathogens. However,atanypointintime,theimmune
system can only circulate a limited number of lymphocytes, and thereby a limited variety
of receptors, through the body. Considering this, it seems crucial that the immune system
optimizesthe use of itslimitedresources by somehowplacing its receptors ”strategically”
inthespaceofpossibleshapes.
UsingbothanalyticalandcomputersimulationresultsIshow:
How antibody repertoires optimize their structure for maximal coverage of given
pathogensets;
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The extent to which this optimization occurs as a function of the relative sizes of
pathogenandantibodysets,aswellastheirrelativeratesofevolution;
That the specificity with which individual pathogens are recognized increases only
veryslowlywiththesizeoftheantibodyrepertoire.
I further show that compositional biases responsible for targeting somatic hyper-
mutation to the antigen-binding regions of individual antibody genes appeared very early
in phylogeny. This suggests that evolvability under somatic hypermutation has been an
importantselectionpressureintheevolutionofimmunesystems.
Asacontributiontotheeffortforidentifyingthemechanismresponsibleforsomatic
hypermutation,
Iprovideevidencethatthecompositionalbiasesinnon-immunoglobulingeneswould
minimize the effect of somatic hypermutation in these genes. I propose that the
mechanismsresponsibleforgermlinemutationandsomatichypermutationmightbe
related.
I provide improved methods for estimating mutation rates. The assessment of the
effect that various genetic manipulations have on the rate of somatic hypermutation
canbeimprovedbyusingthesemethods.
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Contents
Abstract v
ListofFigures xi
ListofTables 1
1 Introduction 1
1.1 Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Brief introductiontotheimmunesystem . . . . . . . . . . . . . . . . . . 3
1.2.1 Innateversusadaptiveimmunity . . . . . . . . . . . . . . . . . 3
1.2.2 Thedevelopmentofanimmuneresponse . . . . . . . . . . . . . 4
1.2.3 Self-nonselfdiscrimination . . . . . . . . . . . . . . . . . . . . 6
1.2.4 Theanticipatorycapacityoftheimmunesystem . . . . . . . . . 8
1.2.5 Structuralcomponentsoftheimmunereceptors . . . . . . . . . 12
2 Howmuch cangermlinediversitydo? 15
2.1 Shape spacecoveragewithdistance-dependentmatching . . . . . . . . . 16
2.1.1 Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.1.2 Lowerboundontheevolvedfitness . . . . . . . . . . . . . . . . 21
2.1.3 Upperboundontheevolvedfitness . . . . . . . . . . . . . . . . 21
2.1.4 Thefitnessofevolvedlibraries . . . . . . . . . . . . . . . . . . 22
2.1.5 Thestrategyofevolvedlibraries . . . . . . . . . . . . . . . . . . 24
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2.2 Shape spacecoveragewithothermatchingrules . . . . . . . . . . . . . . 31
2.2.1 Lowerboundonthefitness . . . . . . . . . . . . . . . . . . . . 33
2.2.2 Thefitnessandstructureofevolvedlibraries . . . . . . . . . . . 34
2.2.3 Implicationsforrandomantibodylibraries . . . . . . . . . . . . 35
3 Somatichypermutation targetsthe antigen-binding regionsofantibody genes 39
3.1 Calculatingthepredictedreplacementmutabilityofasequence . . . . . . 43
3.2 All human immunoglobulin -region sequences have higher average re-
placementmutabilityofCDR nucleotidesthanofFR nucleotides . . . . . 44
3.3 Statisticalanalysisonthelevelofindividualsequences . . . . . . . . . . 46
3.4 Contribution of nucleotide composition, codon composition and codon
usagebiastothepredictedFRandCDRreplacementmutabilityofhuman
sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.5 Are human -regionsequencesoptimizedforsomatichypermutation? . . 57
3.6 Similarmutabilitypatternin genesfromotherspecies . . . . . . . . . . 62
3.7 Higher predicted replacement mutability of T cell receptor CDRs than T
cellreceptorFRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4 Non-immunoglobulin genes would have low mutability under somatic hyper-
mutation 70
4.1 Innon-immunoglobulingenes,predictedmutabilityiscorrelatedwithA/T
content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.2 A significant proportion of non-immunoglobulin genes also have codon
biasconsistentwithlowmutabilityundersomatichypermutation . . . . . 74
5 Mutants mustbegenerated andselected inastep-wisefashionduringthe ger-
minalcenter reaction 78
5.1 Affinitymaturationduringthegerminalcenterreaction . . . . . . . . . . 78
5.2 One-passselectionmodelofthegerminalcenterreaction . . . . . . . . . 81
5.2.1 Basicmodel . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
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5.2.2 Amplification of high affinity cells in the memory population is
alogarithmicfunctionoftheirselectioncoefficient . . . . . . . . 84
5.3 Implicationsforaffinitymaturationinthegerminalcenters . . . . . . . . 89
6 Mutation rateestimation 92
6.1 Celldivision,cellcycletimes . . . . . . . . . . . . . . . . . . . . . . . . 92
6.2 Computationalmodelofa growingcultureofcells . . . . . . . . . . . . . 95
6.3 Meannumberofmutantsinacultureofsize . . . . . . . . . . . . . . . 98
6.4 ContinuumapproximationoftheLuria-Delbru¨ckdistribution . . . . . . . 107
6.4.1 Cell-cycle correction to thecontinuumLuria-Delbru¨ckdistribu-
tionfor2-phasemodelsofthecellcycle . . . . . . . . . . . . . 110
6.4.2 Inference procedures. . . . . . . . . . . . . . . . . . . . . . . . 113
6.5 Constructing confidence intervals for the mean mutation rate in cultures
ofcellsthathaveagamma-distributedcellcycletime . . . . . . . . . . . 114
6.6 Estimatingmutationratesinrealcultures . . . . . . . . . . . . . . . . . . 116
6.6.1 Bacterial growth . . . . . . . . . . . . . . . . . . . . . . . . . . 116
6.6.2 Emergenceofhighaffinitymutantsinthegerminalcenters . . . 118
7 Conclusions 122
7.1 Summaryofresults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
7.1.1 Germline diversity does not contribute to the direct recognition
ofpathogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
7.1.2 Immunoglobulingenes evolved plasticity for somatic hypermu-
tation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
7.1.3 The efficiency of affinity maturation can only be explained by
multipleroundsofmutation-selection-expansionoflymphocytes 125
7.1.4 Improvedmethodsformutationrateestimation . . . . . . . . . . 126
7.2 Futurework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
7.3 Inlieuofclosing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
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A Non-immunoglobulin genes 130
References 136
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