Symbolic Systems Technology

Using formal systems and and reasoning tools to• Understand how things work; why things don’t work• Design, analyze, adapt complex systems

Carolyn TalcottISSSB

2011 November 14

Plan

• What I mean by Symbolic Systems Biology

• Pathway Logic as an example

• Challenges & Opportunities

Elements of Symbolic Systems Biology

• Modeling and analysis of biological systems

• Representation in a formal system / logic

• Executable models

• Use of formal reasoning tools to answer questions

Modeling Issues

• What questions do you want the model answer?

• What can you observe/measure?

• What questions do you really want the model answer?

• What does that mean?

• Explain it to a computer!

Modeling Methodology

Impact

rapid prototyping

state space search

S |=! model

checking

What is a formal system?

• Language: to describe things and properties

• Semantics: thing satisfies property

• Reasoning principles: proving/disproving properties of things

• [Reflection: to model and reason about models and reasoning]

• Executable formal models (ala model train, airplane, ...)

• System state: collections of entities (name,location,knowledge,resources..)

• System behavior: transition rules, response to stimuli

• Execution: application of rules, possibly concurrent--watch it run, po

• Executions are objects that we can reason about

• Properties of states (P,Q) and executions (ϕ: P until Q, eventually P, this event depents on that event )

Symbolic analysis -- answering questions

• Forward collection -- upper bound on possible states

• Backward collection -- initial states leading to states of interest

• Search -- for states of interest

• Model checking -- do all executions satisfy ϕ, find counter example

• Constraint solving -- steady state analysis

Model Transformations: new views, faster analysis

• Mapping of formal systems

• access to tools (RWL to Petri Nets)

• alternative semantics (qualitative, kinetic, probabilistic/stochastic)

• richer property specification (RWL to HOL)

• Abstracting

• quantities (points to regions)

• qualities (phos(Y 123) vs phosY vs phos vs act/inact)

• entities (protein vs family or homology class)

• Canonical form -- to combine/compare models

Pathway Logic (PL) http:pl.csl.sri.com

•Essence•Examples• Response to Stimuli• Bacterial Protease Network• TB metabolic network • Sleep

In a nutshell

• Represented in rewriting logic, mapped to Petri nets for model checking

• Queryable formal knowledge base of experimental findings (Datum KB)

• subject, assay, treatment, times, cells, result, variants, source

• Algebraic signature ~ controlled vocabulary linked to standard sources (Uniprot ...).

• Terms represent reference entity with modifications, activity state, location

• Global model: network of executable rules (RKB) inferred from Datum KB

• Local Model ~ initial state (experimental setup) + relevant rules from RKB

• Pathways (sets of biomolecules that function together) and regulation effects discovered by asking questions (answered by formal reasoning tools)

Answering questions using PL Assistant

• Specify goals and avoids

• Find subnet

• backward collection followed by forward collection

• Find pathway

• assert goal not achievable and ask LoLA, pathway is counter example

• In silico knock outs

• Comparing networks

• Following connections

• Find all rule minimal pathways (separate tool, to be integrated)

• cluster

• ask for essential rules/occurrences, uses

Signaling response to Egf (AMK)

Two ways to activate Erk

Datum query

V9V7V8

V12

V10

V11

V22

V23

V19

V21

V20

V24

V40

V41

V37

V39

V38

V42

V28

V29

V25

V27

V26

V30

V46

V47

V43

V45

V44

V48V3V1V2V6V4V5

V16

V17

V13

V15

V14

V18

V34

V35

V31

V33

V32

V36

V78

V77

V76

V74

V75

V50

V68

V73

V72

V71

V69

V70

V67

V66

V65

V63

V64

V49

V57

V62

V61

V60

V58

V59

V112

V113

V109

V111

V110

V114

V142

V143

V139

V141

V140

V144

V106

V107

V103

V105

V104

V108

V136

V137

V133

V135

V134

V138

V100

V101

V97

V99

V98

V102

V130

V131

V127

V129

V128

V132

V94

V95

V91

V93

V92

V96

V124

V125

V121

V123

V122

V126

V54

V55

V51

V53

V52

V56

V82

V83

V79

V81

V80

V84

V88

V89

V85

V87

V86

V90

V118

V119

V115

V117

V116

V120

050

100

150

200

Cluster Dendrogram

hclust (*, "ward")

dataDist

Height

All ways to activate Erk (144), clustered

Essential rules cluster 1 (green)

RapA-inhib-CLc

81

MurAA-CLc

45

MurAA-degraded-CLc

CiaRH-CLc

142140

40

MecA-degraded-CLc

101

Mpr-gene-on-CLc

99

Bpr-gene-on-CLc

97

NprE-gene-on-CLc

181

SpoIVFB-inhib-CLm

RapA-CLc

80

BofA-CLm

103

NprB-gene-on-CLc

SpoIVFB-CLm

182180

proPhrA-XOut

112114

PhrA-XOut CSF-XOut

115

PhrG-CLc

120

CtsR-degraded-CLc

43

DegS-CLc

122

DegU-phos-CLcCtsR-CLc

68 52

50

51

FtsH-gene-downreg-CLc

RapE-inhib-CLc

PhrE-CLc

193

30

ClpE:ClpP-CLcRapF-inhib-CLc

PhrF-CLc

194

ClpE-CLc

64

RapA-gene-CLc

155

RapA-gene-downreg-CLc

31

ClpC:ClpP-CLc

RapG-CLc

121

33

109

Epr-gene-on-CLc

RapG-inhib-CLc

ClpP-gene-on-CLc

SpoJ-gene-on-CLc

SpaA-CLw

23 22

Heme:IsdG-CLc

18

113

PhrA-CLc

SigmaA-CLc

61 606291

58

SipV-gene-downreg-CLc

ClpC-gene-on-CLc

35394142 38 37189

44

47 48 49 46

17

Fe3+-CLc

124

SipT-gene-on-CLc

56

SipT-gene-downreg-CLc

Heme:IsdI-CLc

RapE-CLc

79

HtrA-gene-on-CLc

SipV-gene-CLc

57

SipS-gene-downreg-CLc

Abh-CLc

126

SipS-gene-on-CLc

Abh-gene-on-CLc

136

LytE-degraded-CLw

173

LytE-CLw

174 171

LytF-degraded-CLw

59

Lsp-gene-downreg-CLc pre-AmyQ-CLm

130129 128

FtsZ-CLc

158160 163 161 159 162

LytF-CLw

172

Lsp-gene-CLc

167

LonB-gene-on-CLc

SigmaB-inhib-CLcFtsZ-inhib-CLc

165

SigmaH-degraded-CLc

29

ClpP:ClpX-CLc

36

164

ClpX-CLc

54

EzrA-CLm

157

LonA-CLc

166

SigmaG-inhib-CLc

93

Spo0A-CLc

SigmaB-CLc

63 67 176175178179

89

Spo0B-phos-CLc

Spo0F-CLc

90

Spo0B-CLcSpo0A-phos-CLc

ClpX-gene-downreg-CLc

55

73

SpoIIAA-gene-on-CLc

ClpX-gene-CLc

SpaA-anchored-CLw

24

SrtF-CLm

EzrA-degraded-CLm

SigmaW-CLc

2527 32

FosB-gene-on-CLcFtsH-gene-on-CLc

SecY-CLm

71

MecA-CLcSecY-degraded-CLm

pre-PrsA-CLm

131

ComA-CLc

146

75

Spo0A-gene-on-CLc

PrsA-CLm

138

156

CodW:CodX-CLc

Spo0E-degraded-CLc

SrfA-gene-on-CLc

AmyQ-XOut

Lsp-CLm

105

Vpr-gene-on-CLc

SigmaH-CLc

pbpE-gene-on-CLc

107

WprA-gene-on-CLc

SigmaH-act-CLc

CodW-CLcCodX-CLc

72

SpoIIE-gene-on-CLc

186

SpoIIAB-gene-on-CLc

190

SpoIIAA-CLc

SpoIIAA-phos-CLc

183

SpoIVFA-cleaved-CLm

SpoIVB-CLc

Vpr-XOut

116

Vpr-gene-CLc

147

SrfA-gene-CLc

SrfA-CLc

106

145

143

SpoJ-gene-CLcSpoJ-CLc

108

SigmaK-CLc

pro-SigmaK-CLm

Heme:IsdA-anchored-CLw

13

DegU-degraded-CLc

YwbN-gene-CLc

133

134

YwbN-CLc

KinE-CLc

88

28

PBP4-CLmWprA-gene-CLc

KipI-inhib-CLc

WprA-CLw

Spo0F-phos-CLc

YwbN-gene-on-CLc

84

KipA-CLc

Lipid-II-bound-CLw

Lipid-II-CLm

21

SigmaG-CLc

pbpE-gene-CLc

70

9

Heme:IsdC-anchored-CLw

IsdH-anchored-CLw

ComK-degraded-CLc

ComS-CLc

IsdA-anchored-CLw

10

IsdB-anchored-CLw

11

7

ComS-degraded-CLc

AbrB-gene-downreg-CLc

111 95 96

135

AbrB-gene-CLc

AbrB-CLc

119

AprE-gene-downreg-CLc ClpC-gene-downreg-CLc ClpP-gene-downreg-CLc

McsA-CLc

53

Spx-CLc

McsB-CLc

Spx-degraded-CLc

SigmaX-CLc

132

195

SinR-CLc

118123

AprE-gene-on-CLc

proCSF-XOut

Parks-nucleotide-CLc

19

Undecaprenyl-phosphate-CLm

Lipid-I-CLm

20

MraY-CLm

SpaB-CLwSpaC-CLw

SpaABC-pilus-Sig

Hpr-CLc

117

RapF-CLc

SpoIVFA-CLm

184

151

ComK-gene-on-CLc

CtpB-CLc

153

DegU-CLc

150

ComK-gene-downreg-CLc

110

Epr-XOut Epr-gene-CLc

26

FosB-CLcFosB-gene-CLc

69

FtsH-CLm FtsH-gene-CLc

94

ClpC-gene-CLc

66

ClpC-CLc

65

ClpP-CLcClpP-gene-CLc

152

ComK-CLc

ComK-gene-CLc

100

Bpr-XOutBpr-gene-CLc

77

AprE-XOut AprE-gene-CLc

Abh-gene-CLc

125 127

SipS-gene-CLc SipS-CLmSipT-CLmSipT-gene-CLc

SpeB-gene-on-CLc

170

proSpeB-XOutSpeB-gene-CLc

76

137169

144

RapD-gene-CLcRapD-CLc

154

SigmaF-CLc

188

SigmaF-gene-on-CLc

192

SigmaF-gene-CLc

SigmaF-act-CLc

191

Sporulation-Sig

104

NprB-gene-CLc NprB-XOut

102

Mpr-XOutMpr-gene-CLc

RapD-gene-on-CLc

148 149

NprE-gene-CLc

98

NprE-XOut

LonB-CLc

168

HtrA-CLm

139

141

HtrA-gene-CLc

LonB-gene-CLc

12

Heme:IsdE-CLm

1615

IsdI-CLcIsdG-CLc

IsdH-CLw

3

814

IsdC-anchored-CLw

SigmaW-act-CLc RsiW-degraded-CLm

KinA-inhib-CLc

KipI-CLc

83

KinA-CLc

82

IsdD-CLm IsdF-CLm

YwlE-CLc

ClpC-inhib-CLc YpbH-CLc

UDP-GlcNAc-CLc

1

SrtA-CLm

2

MurG-CLm

IsdB-CLw

IsdC-CLw

4

SrtB-CLm IsdE-CLm

SpoIIAB-degraded-CLc

YjbH-CLc

74

SpoIIE-CLmSpoIIE-gene-CLc

187

SpoIIAB-gene-CLc SpoIIAB-CLc

185

SpoIIAA-gene-CLc

RsiW-CLm

RsbW:SigmaB-CLc

RsiW:SigmaW-CLc

92

Spo0E-gene-CLcSpo0E-CLc

Spo0E-gene-on-CLc

Spo0A-gene-CLc

KinB-CLm

85

KinC-CLc

86

78

87

KinD-CLc

PrsW-CLmSigmaF:SpoIIAB-CLc

SepF-CLc

FtsZ:SepF-CLc

RsbU-CLc

SigmaB-act-CLc

RsbT-CLc RsbW-CLc

177

RsbW:RsbV-CLc

RsbV-CLc

YlmF-CLc

FtsZ:SpoIIE-CLm FtsZ:ZapA-CLc

ZapA-CLc

FtsZ:YlmF-CLcDegU-inhib-CLc

RapD-gene-downreg-CLc

RsbS-CLc

FtsZ:FtsA-CLc

RghR-CLcRopB-CLc

pbpE-gene-downreg-CLc

FtsL-degraded-CLm

FtsL-CLm

34

RasP-CLm

FtsA-CLc

StreptolysinS-inhib-XOut

6

Heme:IsdH-anchored-CLw

StreptolysinS-XOut RapC-gene-CLc

RapF-gene-downreg-CLc

RapF-gene-CLc

RapC-gene-downreg-CLcSrfA-gene-downreg-CLc

IsdA-CLw

IlvB-degraded-CLc

IlvB-CLc

SpeB-XOut

GlmS-CLc

GlmS-degraded-CLcPurF-degraded-CLc

PurF-CLc PyrB-CLc

PyrB-degraded-CLc

RapB-CLc

5

Heme:IsdB-anchored-CLw

Heme-XOut

initial states

possible reachable states

transition/rules

consumed/produced

enzymatic relation

106

FtsH-CLm

Spo0A-gene-on-CLc

75

93

Spo0E-degraded-CLc

90

Spo0B-CLc

Spo0B-phos-CLc

Spo0E-CLc

76

Spo0A-CLc

Spo0A-gene-CLc

Vpr-XOut

Vpr-gene-CLc

Vpr-gene-on-CLc

103 97

Epr-gene-on-CLc

99

Epr-XOut

110

Epr-gene-CLc

Spo0A-phos-CLc

NprE-gene-CLcNprE-

XOut

109

NprE-gene-on-CLc

104

NprB-gene-CLc

Bpr-gene-CLc

100

Bpr-gene-on-CLc

Bpr-XOut

98

Mpr-gene-on-CLc

101105

Mpr-gene-CLc

102

NprB-gene-on-CLc

NprB-XOut Mpr-

XOut

Protease interaction network (Gram Positive Bacteria) (Anupama) What regulates a protease,

what does it regulate

What happens if you knockout FtsH?

Multiple synthesis routes

TB-mycolic-acid synthesis (Malabika)

A HypotheticaL Model PathwayRelating State and Synaptic Plasticity

Wake state: unknown signal(s) => phosphorylation of Rock1 => activation of Limk1 => phosphorylation of cofilin => increase in polymerized actin (Phosphorylated cofilin is unable to depolymerize actin)

SWS:RhoDG11 binds Rhob-GDP (is not phosphorylated) => Rock1, Limk1, and cofillin would not be phosphorylated and => actin depolymerization => decrease in synaptic weight

Challenges and Opportunities

We need good models not just good analysis tools

• Alternative computational methods to check a prediction (example: proximity)

• Type checking: using basic biological knowledge

•P has TS phosphorylation sites, Q is a tyrosine kinase

•A rule that says Q phosphorylates P is either wrong or missing intermediate steps

• Better ways to capture experimental data.

•Semantic data mining

•Symbolic supplementary data

• Inferring rules from experimental data.

•Needs representation of relevant biological knowledge

•What do experiments tell you?

•Roles -- adaptor, scaffold, transformer

Model Integration

• Aggregation -- different representation of the same process

• PID EgfR signalling + Reactome EgfR signalling

• Complementation -- different parts of a response

• Making a model executable

• Reactome pathways are disconnected -- missing rules, multitple levels of detail -- when are two entities the same?

• Mutiple computational models

• multi scale

• qualitative + quantitative

Complexity

• Query of complex models may give complex answers (all paths)

• How to visualize, make sense of the results

• Scaling

• Divide and conquer

• Property preserving abstractions

• zooming in and out

Synergy

• Finding a shared representation of relevant biological knowledge

• Combining results from multiple analyses

• how can our different tools work together?

• Biologist friendly scripting

The end! (The beginning?)