Appendix I.1. The lac operon control circuit.
To feed E. coli growth, glucose undergoes a series of biochemical transformations known as glycolysis (literally, “sugar breaking”) followed by oxidation through the Krebs cycle. These transformations produce both precursors for building other cell molecules and high-energy compounds that provide the chemical fuel for a wide variety of essential cell activities. To metabolize lactose for growth, E. coli utilizes both glycolysis and the Krebs cycle but requires additional biochemical capabilities to convert lactose into glucose. These activities include an enzyme (LacZ) that splits lactose into glucose and galactose and a cell membrane protein (LacY) that transports lactose into the cell (Jacob and Monod 1961). While the enzymes for glucose utilization are present under most growth conditions, LacZ and LacY appear only when the bacteria grow on lactose (Monod and Cohn 1952). Thus, their synthesis is regulated according to nutritional conditions, and expression of the corresponding DNA sequences lacZ and lacY is subject to a control circuit that has been largely deciphered over the past five decades.
When lactose utilization was first studied genetically, in the late 1940s and early 1950s, mutations affecting it clustered as a single point on the genetic map of E. coli:
As biochemical and genetic
analysis advanced, Monod et al. found that lacZ
and lacY constitute a contiguous structure in
the E. coli DNA, together with lacA
that encodes the coregulated acetylase
which detoxifies aromatic beta-galactosides from plants. They
called the entire genetic structure “the lac
operon” because it operates as a coordinated system (Jacob, Perrin et
al. 1960). By 1961, the operon was known to
contained four coding sequences (lacI encoding
repressor, lacZ encoding beta-galactosidase,
lacY encoding galactoside permease, and lacA encoding galactoside acetylase) plus a
regulatory site, lacO or the “operator,”
which controlled expression of lacZYA (Jacob and Monod
Over the next two decades, additional control sites and regulatory proteins were identified: the CRP protein (cyclic AMP receptor protein) and its cognate CRP binding site, the lacP promoter which was the starting site for transcription, and two additional operator sites, one of which resides inside the lacZ coding sequence (Scaife and Beckwith 1966; Arditti, Scaife et al. 1968; Silverstone, Magasanik et al. 1969; Muller, Oehler et al. 1996).
Expressing the lacZYA operon requires two proteins: (i) RNA polymerase that transcribes the DNA into a messenger RNA for further translation into LacZ and LacY proteins by the cell’s ribosomes and (ii) CRP (“cyclic AMP receptor protein”) which stimulates the initiation of transcription by the polymerase (Inada, Kimata et al. 1996; Kimata, Takahashi et al. 1997; Kuhlman, Zhang et al. 2007). Whether or not expression occurs is under the control of three additional molecules: (iii) the LacI repressor (I for “inducibility”) Willson, 1964 #964, (iv) an allolactose inducer molecule produced from lactose by the action of LacZ (Huber, Wallenfels et al. 1975; Huber, Kurz et al. 1976; Friedman, Olson et al. 1977; Turner and Huber 1977; Wu, Bahl et al. 1978) and (v) cyclic AMP (cAMP), a derivative of ATP that must bind to CRP before it can stimulate transcription (Inada, Kimata et al. 1996; Kimata, Takahashi et al. 1997).
A key point is that the system works properly because lac operon DNA contains specific short binding
sequences for LacI repressor (“operators” = lacO),
for RNA polymerase (“promoter” = lacP) and
for CRP (“crp site”). When there is no lactose
(and hence no inducer), LacI binds to a pair of lacO
sites and prevents RNA polymerase from gaining access to lacP, where it has to bind to initiate
transcription of lacZ and lacY.
When inducer is present, LacI binding to lacO
sites no longer blocks polymerase access. By itself,
polymerase recognizes lacP weakly, and
physiologically significant transcription from lacP
requires simultaneous binding of a complex between cAMP and
CRP to the crp site (De Crombrugghe,
Chen et al. 1971; De Crombrugghe, Chen et al. 1971; Nisseley, Anderson et al. 1971; Pastan and Perlman 1972). Interaction
between CRP and polymerase stabilizes binding to lacP
and thus enhances transcription (Savery, Rhodius et
al. 1996). In the absence of cAMP, CRP
cannot bind to crp. These binding sites for
protein recognition (lacO, lacP and crp) must be properly positioned for all these
regulatory interactions to occur correctly. In essence, they
format the DNA for regulation and controlled access to genomic
protein coding information.
The level of cAMP in the E. coli cell is controlled by the availability of glucose in the external medium (Inada, Kimata et al. 1996; Kimata, Takahashi et al. 1997). Since cAMP is necessary for significant levels of lac operon transcription, it connects the regulatory circuit to recognition of one of the two sugars. The glucose control of cAMP levels occurs through one of the glucose transport proteins at the cell membrane (Harwood, Gazdar et al. 1976; Peterkofsky 1988). When glucose is available, the transport protein transfers a negatively charged phosphate group to the entering sugar, thus trapping it inside the cell and feeding it into the glycolytic process. This transport molecule is named “Protein IIAGlc” of the phosphotransferase system (PTS) discovered by Saul Roseman in 1964 (Kundig, Ghosh et al. 1964; Roseman 1969). The superscript “Glc” indicates that this particular PTS protein II specifically recognizes glucose (Simoni, Levinthal et al. 1967; Stock, Waygood et al. 1982). When there is no glucose available outside the cell, this protein accumulates in a form carrying an attached phosphate group, and this phosphorylated transport protein stimulates the enzyme that converts ATP into cAMP. Via this series of interactions, the cAMP levels inside the cell inversely reflect the glucose levels outside the cell. The glucose transport protein thus serves a dual function in both trapping glucose inside the cell and sensing extracellular glucose. Note, in a similar vein, that through the series of reactions leading up to derepression, LacY, LacZ and LacI repressor constitute a sensory circuit for lactose.
All of the reactions just summarized can be restated in a small number of Boolean (if X, then Y; or X ==> Y) propositions to compute the following specific and nontrivial regulatory algorithm: transcribe lacZ and lacY from lacP if, AND ONLY IF, glucose is NOT available and lactose IS available:
Since this formulation of lac operon control circuits was elaborated
several years ago, there has been a challenge to the role of
cAMP and CRP in establishing diauxic growth (Crasnier-Mednansky
2008; Narang 2009; Narang 2009). The
alternative explanation for glucose utilization prior to
lactose consumption is the observation that glucose is able to
inhibit transport of lactose into the cell by low uninduced
levels of LacY permease. That interpretation fails to explain
the observation that addition of cAMP abolishes the diauxic
growth pattern (Perlman and Pastan
1968; De Crombrugghe,
Perlman et al. 1969; Perlman, De Crombrugghe et al. 1969; Pastan and Perlman 1970). It may well
be that the two regulatory effects reinforce each other, in a
“fuzzy logic” manner (Kosko and Isaka 1993).
Appendix I.2. S. cerevisiae pheromone response signal network (Sprague 1991).S. cereviseae a cells contain a dedicated Ste2 a-pheromone receptor in their cytoplasmic membrane which belongs to a large family of “heterotrimeric G factor-coupled” receptors (Blumer, Reneke et al. 1988; Nomoto, Nakayama et al. 1990; Josefsson 1999; Dohlman and Slessareva 2006; Koelle 2006; Slessareva and Dohlman 2006; Yin, Shumay et al. 2006). What this fancy name means is that the receptor binds to a three-subunit protein that hydrolyzes GTP and dissociates into its three separate components (Ga, Gb = Ste4 and Gg = Ste18) in response to receptor binding (Dohlman 2002). (The membrane receptor is called Ste2 and the G factor components Ste4 and Ste18 because mutants lacking any of them are sterile and unable to mate.) When a-pheromone binds to Ste2, the G factor dissociates and liberates a Ste4/Ste18 heterodimer (2 subunit protein). This heterodimer, in turn, binds to the Ste5 scaffold that holds three proteins that sequentially transfer a phosphate group in a widespread signaling system called a “MAP kinase (MAPK) cascade” (van Drogen and Peter 2001; Wang and Dohlman 2002; Wang and Dohlman 2006; Paliwal, Iglesias et al. 2007; Hu, Rappel et al. 2009). Each MAP kinase cascade works by transferring a phosphate group along a chain of MAPKKK (MAP kinase kinase kinase), MAPKK (MAP kinase kinase) and MAPK (MAP kinase) proteins which can then direct the phosphorylation process to other targets (Gustin, Albertyn et al. 1998; Mishra, Tuteja et al. 2006; Schwacke and Voit 2007) (Wang and Dohlman 2006; Chen and Thorner 2007) (Hu, Rappel et al. 2009). The Ste4/Ste18 heterodimer activates the protein phosphorylation cascade by stimulating Ste20 to phosphorylate Ste11 (MAPKKK) (Lee and Elion 1999), which then phosphorylates Ste 7 (MAPKK), which then phosphorylates the Fus3 MAPK molecule (Kusari, Molina et al. 2004). Fus3 phosphorylates and thereby activates the Ste12 transcription factor to stimulate mating function expression (Song, Dolan et al. 1991; Kirkman-Correia, Stroke et al. 1993; Chou, Lane et al. 2006; Esch, Wang et al. 2006)[Wong Sak Hoi, 2010 #6121]. Fus3 also phosphorylates and activates the Far1 inhibitor of the cell cycle function needed to exit G1 (Dolan 1996). Other less well characterized phosphorylations presumably play a role in initiating shmoo-like growth (Chenevert 1994; Chenevert, Valtz et al. 1994; Samaj, Baluska et al. 2004; Lesage and Bussey 2006; Arkowitz 2009; Aguilar, Heiman et al. 2010).
Appendix II.1. Formatting the genome for transcriptional control.
Transcriptional control signals bind a wide variety but finite number of different regulatory proteins, or “transcription factors” (Hickey, Conway de Macario et al. 2002; Wang and Dohlman 2006; Hughes and Friedman 2007; Pinney, Amoutzias et al. 2007; Haerty, Artieri et al. 2008; Shan, Zahn et al. 2009; Gramzow, Ritz et al. 2010). Some of these factors are specialized, like the LacI repressor protein; others are more general and regulate families of interconnected functions, like the CRP protein; and other proteins are used by a significant proportion of all coding sequences, like RNA polymerase and (in eukaryotes) associated “basal transcription factors.”
The distribution of the corresponding recognition signals through the genome falls correspondingly into a range of classes: some unique to one or a small number of loci, like lacO operators; some present at several to many sites, like the crp binding sites; and some very widespread, like the promoter sequences that direct RNA polymerase to the initiation site for transcription (Jaeger, Chan et al. 2010). Even widespread signals, like promoters, can fall into more specialized classes; these classes facilitate the expression of coordinated suites of coding sequences required under special sets of conditions, such as high temperature “heat shock” and other stresses (Wallrath, Lu et al. 1994; Arsene, Tomoyasu et al. 2000; Pirkkala, Nykanen et al. 2001; Hengge-Aronis 2002; Klauck, Typas et al. 2007). Special promoter signals are also utilized for the expression of complex functions requiring transcription of many coding sequences, such as cell differentiation. In prokaryotes, which have highly condensed genomes, transcription signals are often found within the protein coding sequences. For example, one of the three lacO operators is located within the lacZ coding sequence.
Transcriptional control signals operate in combinations that facilitate regulatory interactions between the corresponding transcription factors. Several key regions of coding sequences hold the binding sites: the promoter area around the start site for transcription, the area around the termination site for ending transcription, and more distant locations that interact with the promoter area through DNA looping to bring them into proximity (Tjian 1995). These distant regions have received a variety of names (‘enhancer.” “silencer,” “upstream activating sequence”) according to whether they stimulate or repress transcription, but the term “enhancer” has found the most general application (Grimm and Nordeen 1999; Veitia 2008). Enhancers contain clusters of binding sites and are generally functional wherever they are located within distances of thousands or sometimes tens of thousands of base-pairs from the regulated coding sequences. In eukaryotes, which have interrupted coding sequences, enhancer elements, are often found in introns, which are spliced out of the final protein-coding messenger RNA (mRNA).
Transcription control signals in eukaryotes assemble hierarchically into larger complexes that have been given the generic description of “cis-regulatory modules” (CRMs) (Ben-Tabou de-Leon and Davidson 2007; Hinman, Nguyen et al. 2007; Bonn and Furlong 2008; Ben-Tabou de-Leon and Davidson 2009; Ho, Johnsen et al. 2009; Li and Davidson 2009; MacArthur, Li et al. 2009; Zinzen, Girardot et al. 2009; Borok, Tran et al. 2010). These CRMs can extend for many thousands of basepairs in the genome and typically contain multiple enhancer regions that are independently active at different times in the cell cycle, at different phases or tissues of multicellular development, or in response to distinct stimuli. This hierarchical architecture facilitates the execution of complex regulatory algorithms in morphogenesis and of multivalent responses to inputs, such as DNA damage or binding of intercellular signaling molecules (Cooper, Loose et al. 2009). By analogy with the multivalent allosteric nature of proteins, the composite CRMs constitute a type of microprocessor element. Although protein microprocessors can function at different locations in the cell and thoughout the genome, the action of CRMs is typically limited to nearby regions of the genome and the coding sequences they contain. In combination, CRMs and the transcription factors they bind can generate an enormous variety of genomic responses to input signals.
Transcription factors are dynamic proteins that regulate the expression of other transcriptions (and of themselves, as well) through binding to the CRMs adjacent to their coding sequences. These feedback interactions and the networks they form permit cells to construct complex regulatory circuits that process a large number of inter- and intracellular signals to compute an appropriate transcriptional response (Mangan and Alon 2003; Amoutzias, Robertson et al. 2004; Levine and Davidson 2005; Davidson and Erwin 2006; Madan Babu, Teichmann et al. 2006; Alon 2007; Balaji and Aravind 2007; Madan Babu, Balaji et al. 2007; Gonzalez Perez, Gonzalez Gonzalez et al. 2008; Aravind, Anantharaman et al. 2009; Hinman, Yankura et al. 2009). How these transcription factor circuits operate has been partially deciphered in certain model systems, such as the developing sea urchin, the progressive segmentation of the early Drosophila embryo and the establishment of anterior-posterior (AP) and dorsal-ventral (DV) axes in animal development (Nusslein-Volhard and Wieschaus 1980; Davidson and Erwin 2006; Erwin and Davidson 2009) and (De Robertis, Oliver et al. 1990; Nusslein-Volhard 1996).
Appendix II.2. Natural genetic engineering in B lymphocytes for the rapid evolution and maturation of a virtually infinite diversity of antigen-binding proteins.Antibody structure. To clarify the discussion, it is necessary to describe some essential features of the antibody proteins and introduce basic terminology. I apologize to the reader for the proliferation of symbols, but that is inevitable when we have to deal with a system that has a virtually infinite number of outcomes. With a little patience, the description will all make sense and show how infinity is achieved in the real world of the B lymphocyte.
V(D)J joining. There are no functional antibody coding regions transmitted in the mammalian germ line. Each expressed antibody locus has to be constructed from partial sequence components in the germ line chromosomes. The details of the construction process generate the immense variety in antigen recognition pockets that is needed for effective detection of foreign invaders (Gellert 1997; Shapiro 2005).
Structure of immunoglobulin-coding DNA and the process of V(D)J joining. The different V, D, J and C exons and the details of the molecular events are explained in (Bassing, Swat et al. 2002)and (Gellert 2002). The differently shaded triangles represent complementary recombination signal sequences (RSSs). For any two exons to join together, they must be flanked by complementary RSSs. Two identical RSSs will not promote DNA breakage and rejoining. Note, in the heavy chain chromosome, how the arrangement of RSSs prevents V-J and D-D joining and effectively prevents further joining activity on the fully rearranged chromosome. The shaded rectangle in the VHj-DHj joining product indicates a segment of “N region” untemplated nucleotides arising from the action of terminal transferase before the broken fragments are ligated together. From (Shapiro 2005) with permission.Men and mice have two kinds of L chains, labeled Kappa (Lk) and Lambda (Ll). For each class of L chain, the germ line contains a single C region exon separated by introns from a set of four short join (J) region exons (JL1, JL2, JL3, JL4). Immediately upstream of the J region exons, no functional transcription signals are present. A considerable distance upstream are a set of about 100-300 V region exons preceded by suitable transcription signals (Vl1, Vl2…V li, V lj…V ly, V lz). A functional L chain coding sequence is constructed by joining one of the V regions to one of the J regions. The joined VJ exon can then be transcribed, and RNA splicing constructs a functional VJC coding sequence that can be translated into an L chain. It should be clear that different Vli –Jln and Vki –Jkn combinations can generate about 400-1200 different L chains of each class.
We do not
fully understand the somatic hypermutation process or how it is
targeted, but a few informative details have been established (Papavasiliou
and Schatz 2002).
(i) The activated B cells synthesize an “activation-induced cytidine deaminase” (AID) enzyme that is essential for somatic hypermutation (Muramatsu, Kinoshita et al. 2000; Longerich, Basu et al. 2006). AID removes amino groups from C nucleotides in single-stranded DNA and converts them into Us, which are targets for base-excision repair. We hypothesize that AID action recruits repair functions, possibly including mutator polymerases (Cascalho, Wong et al. 1998; Diaz and Storb 2003; Seki, Gearhart et al. 2005; Goodman, Scharff et al. 2007; Liu and Schatz 2009), to participate in somatic hypermutation.
(ii) Somatic hypermutation depends on transcription from the immunoglobulin start signals and extends about 2 kb from the start site (Inlay, Gao et al. 2006). If other DNA sequences are placed downstream of the start site, then they are subject to hypermutation, and if the start site is moved next to the C region, then it is mutagenized. Thus, transcription is necessary for somatic hypermutation and acts in coordination with AID, almost certainly because the two DNA strands are separated during transcription (Ramiro, Stavropoulos et al. 2003).
(iii) A 9.8 kb sequence has recently been characterized that is essential for somatic hypermutation (Blagodatski, Batrak et al. 2009). This “diversification activator” (DIVAC) DNA segment lies downstream of the mutagenized V region and activates hypermutation when placed downstream of non-immunoglobulin loci in activated B cells. DIVAC appears to have a complex structure, and its mechanism of stimulating hypermutation is unknown. Since we know that AID works broadly around the genome in activated B cells, we may speculate that DIVAC somehow blocks the error-free repair that prevents hypermutation outside the immunoglobulin loci (Liu and Schatz 2009). The existence of DIVAC provides at least the beginnings of an explanation for the restriction of somatic hypermutation to immunoglobulin V region sequences.
The theoretical significance of somatic hypermutation is two fold, First, it demonstrates that cells can coordinate transcription signals, DNA-modifying activities like AID, and signals such as the DIVAC element to target highly localized and functionally relevant mutagenesis to a specific genome locus. This capacity has long been denied in conventional evolutionary thinking, and most evolutionists would treat somatic hypermutation as extraordinary and not of general significance. Nonetheless, the fact remains that living cells can, and do, carry out targeted mutagenesis. Consequently, this capability has to be incorporated into evolutionary thinking. The second significance of somatic hypermutation is that it demonstrates that rapid protein evolution occurs in two steps: (i) initial invention of the antigen-binding molecule by V(D)J joining and (ii) subsequent fine-tuning by targeted mutagenesis. This switch between macroevolution to produce something totally novel followed by microevolution to make the novelty work more efficiently may well be paradigmatic for evolution in general.
The conceptual importance of class switching lies in the demonstration that DS breaks can be targeted by lymphokine-directed transcription (Honjo, Kinoshita et al. 2002; Sellars, Reina-San-Martin et al.). The integration of intercellular signaling and the transcription it controls with DS breaks and NHEJ provides us with a detailed molecular mechanism for the way communication molecules can direct DNA rearrangements to particular regions of the genome. This is yet another capacity for controlling natural genetic engineering functions that has to be incorporated into our ideas about the genome restructuring tools available for evolution.
Class switch recombination, from (Shapiro 2005) with permission.
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