1 Field-control, phase-transitions, and life’s emergence 2 3 4 Gargi Mitra-Delmotte 1* and A.N. Mitra 2* 5 6 7 139 Cite de l’Ocean, Montgaillard, St.Denis 97400, REUNION. 8 e.mail : [email protected] 9 10 2Emeritius Professor, Department of Physics, Delhi University, INDIA; 244 Tagore Park, 11 Delhi 110009, INDIA; 12 e.mail : [email protected] 13 14 15 16 17 18 19 *Correspondence: 20 Gargi Mitra-Delmotte 1 21 e.mail : [email protected] 22 23 A.N. Mitra 2 24 e.mail : [email protected] 25 26 27 28 29 30 31 32 33 34 35 Number of words: ~11748 (without Abstract, references, tables, and figure legends) 36 7 figures (plus two figures in supplementary information files). 37 38 39 40 41 42 43 44 45 46 47 Abstract 48 49 Critical-like characteristics in open living systems at each organizational level (from bio- 50 molecules to ecosystems) indicate that non-equilibrium phase-transitions into absorbing 51 states lead to self-organized states comprising autonomous components. Also Langton’s 52 hypothesis of the spontaneous emergence of computation in the vicinity of a critical 53 phase-transition, points to the importance of conservative redistribution rules, threshold, 54 meta-stability, and so on. But extrapolating these features to the origins of life, brings up 55 a paradox: how could simple organics-- lacking the ‘soft matter’ response properties of 56 today’s complex bio-molecules--have dissipated energy from primordial reactions 57 (eventually reducing CO 2) in a controlled manner for their ‘ordering’? Nevertheless, a 58 causal link of life’s macroscopic irreversible dynamics to the microscopic reversible laws 59 of statistical mechanics is indicated via the ‘functional-takeover’ of a soft magnetic 60 scaffold by organics (c.f. Cairns-Smith’s “crystal-scaffold”). A field-controlled structure 61 offers a mechanism for bootstrapping-- bottom-up assembly with top-down control: its 62 super-paramagnetic colloidal components obey reversible dynamics, but its dissipation of 63 magnetic (H)-field energy for aggregation breaks time-reversal symmetry. Its responsive 64 adjustments to environmental changes would bring about mutual coupling between 65 random organic sets supported by it via a self-organized-criticality-like mechanism. 66 Further, these adjustments of a cooperative network could alter its capacity to assist a 67 spontaneous process, thus enabling the selection of the functional configuration. A non- 68 equilibrium dynamics could now drive the kinetically-oriented system (trimming the 69 phase-space of sterically-coupled organics) towards a series of phase-transitions with 70 appropriate replacements “taking-over” its functions. Where available, experiments are 71 cited in support of these speculations and for designing appropriate tests. 72 73 Key words: field-controlled colloids; proto-metabolic cycle; slow driving; long-range 74 correlation; organic “takeover”; phase-transition; feedback 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 1 Introduction 94 95 The implications of minerals in life’s emergence were first envisaged by Goldschmidt 96 (1952) and Bernal (1949); these included concentration (adsorption) and catalysis, 97 besides chirality of organics via association with crystal-surfaces. This motivated many 98 works (see Arrhenius 2003; Carter 1978; Ferris 1999; Hazen and Sverjensky 2010; 99 Jacoby 2002; Lahav 1999; Lambert 2008; Schoonen et al 2004; Seigel and Seigel 1981, 100 and references therein), and inspired scenarios exploring the resemblance of ancient 101 enzyme-clusters to mineral ones in metabolism-first approaches to life’s origins (Cody et 102 al 2000; McGlynn et al 2009; Russell and coworkers (Sect.6.3); Wachtershauser 1988). 103 Hazen (2006) reviews the role of mineral surfaces for assistance at two stages of 104 increasing complexity, viz. (1) the emergence of biomolecules, and (2) the emergence of 105 macromolecular systems. These in turn cover three aspects: (i) possible enhanced self- 106 assembly of lipids in the presence of minerals (Deamer and Pashley 1989; Luisi 1989; 107 Hanczyc et al 2003; Chen et al 2004); (ii) polymerization of amino acids and nucleic 108 acids, (Sowerby 1996; Uchihashi et al 1999; Lahav et al 1978; Ferris 1993; Liu and Orgel 109 1998; Orgel 1998) where Smith (1998) uses channels of zeolites as a packing constraint 110 to help polymerization; and (iii) the selective adsorption onto mineral surfaces, of organic 111 species (Churchill et al 2004; Carter 1978; Lowenstam and Weiner 1989). The latter 112 include chiral molecules (Lahav 1999; Jacoby 2002; Hazen and Sholl 2003), although 113 Hazen (2006) also mentions other mechanisms for chiral selection grouped under 114 determinate vs chance local processes. As a universal determinate influence, he notes the 115 parity violation in beta-decay; for more local ones, the chiral-selective photolysis by 116 circular-polarized synchrotron radiation from neutron stars (Bailey et al. 1998; Podlech 117 1999) or magnetochiral photochemistry (Rikken and Raupach 2000); and at smaller 118 scales the amplification of slight chiral excesses via Bose-Einstein condensation (Chela- 119 Flores 1994), or chiral self-assembly of polymers (Bolli et al. 1997; Lippmann and Dix 120 1999; Saghatelian et al. 2001) or simply crystals (Eckert et al. 1993; Lahav and 121 Leiserowitz 1999). According to Hazen (2006), Cairns-Smith’s (1968) theory is the most 122 extreme form of mineral-based hypotheses positing that clay crystals were the precursors 123 of today’s replicators. 124 125 As we see it, in this two-level scenario, the hosting inorganic layer or the crystal- 126 organization—call it level-I (depicted as a white pin board in Figure 1a), -- offers top- 127 down control and assistance for the bottom-up assembly of organic materials into 128 complex patterns building up from randomly reacting/interacting entities in the ‘guest ’ 129 layer—call it level-II (depicted with coloured beads, lower Figure 1a). In the latter, 130 chemical reactions lead to building blocks, small polymers, proto-metabolic reactions, 131 etc. while weak physical interactions (e.g. Hunding et al 2006) lead to small assemblies. 132 Now, level-I’s own crude functional organization acts as a selection/’trimming’ 133 mechanism for ‘fishing out’ constructs with superior information-propagation capacity 134 from the multitude of species forming at level-II. This leads to a gradual replacement of 135 the inorganic organization by organic modules (coloured pattern, upper Figure 1a), where 136 the latter’s recruitment by a functional system --aided by complementary interactions-- is 137 crucial for their dynamic stability (see Sect.3); conceptually too, this relates structure of 138 the organic module to its function . Also, level-II products favouring propagation of 139 template-information (level-I) enable feedback between the levels. But, compared to hard 140 crystals, a soft fractal organization seems a more natural origin for bio-complexity 141 (Sect.2). To that end, a colloidal-gel scaffold (Sect.6) seems promising as a dynamically 142 stable confining medium compatible with the key role of diffusion-controlled reactions in 143 cellular biochemistry (Kopelman 1989; Konkoli 2009). A gradual ‘takeover’ by organic 144 modules is also easier to visualize via a dynamic inorganic modular organization, e.g. soft 145 colloids (Russell et al 1990), provided one can associate them with a crystal-like 146 organization, towards a formal theory. 147 148 Now, in contrast to mineral-based bottom-up approaches adhering to the “metabolism- 149 first” camp, the crystal-scaffold theory proposes a pre-existing template-organization, and 150 thus upholds the “genes-first” one. The former tells how local mineral-organic 151 interactions can assist guest-level-II reactions, while the latter considers the global 152 aspects, i.e., bio-like functions linked to a cooperative organization of mineral-hosts. 153 Indeed, these are complementary, and roughly correspond to the 2-tier organization of 154 living systems: the control-network-level-I of complex biomolecules (proteins, nucleic 155 acids, lipids, carbohydrates, etc) maps to the hosting functional mineral-organization, and 156 the metabolic network-level-II to the (guest) organic reactions/interactions. In the federal- 157 like anatomy of a living system, each tier/sub-system functions independently—yet 158 constrained by feedback-coupling. Now, the second correspondence-- between guest 159 reactions/interactions and metabolic-network-level-II-- is easier to visualize, but the first 160 one is not so obvious (see Sect.3). And while macroscopic energy flow in the metabolic 161 reaction cycles can be mapped to that in similar organic attractors in abiogenesis, we still 162 need a mapping -- albeit in terms of inorganic matter-- for the control-network (level-I) 163 capable of microscopic energy transactions . This can be seen at the level of the 164 components that can undergo infinitesimal conformational changes to traverse a 165 continuous energy landscape, or even at the global system level, where diverse closely 166 spaced states in genotype-space are accessible via environmental fluctuations. Sure 167 enough, open living systems can harness fluctuations --at component (for work-cycles) 168 and (evolving) system levels—in sharp contrast to technological devices, sealing off 169 external noise. 170 171 Indeed, a self-organized criticality (SOC; Sect.2) mechanism for the slow evolution of 172 environment-susceptible bio-systems (levels I and II) helps understand the emergence of 173 complexity in them, despite the absence of a predictable framework. But in the origins of 174 life, the role of SOC is limited if only guest-level-II processes are to be considered, for 175 proto-metabolic reactions or weak interactions between organics dispersed in random 176 mixtures alone cannot suffice for SOC to be effective. [As for relative orders 177 of magnitude, bond energies involved in covalent bonds vs those for Van der Waals 178 clusters bear the ratio: several eV vs a fraction of an eV (Kreuzer 2005), compared to 179 thermal energy (k BT) of ~ hundredth of an eV]. In the absence of an instructional 180 principle, a random process of putting together simple organic building blocks (or 181 mineral-particle-bound ones), into an intricate informational system would seem futile in 182 view of the negligible probabilities at each step, for one wonders what interactive 183 mechanisms are needed to ensure that random mixtures be stable enough to stay together 184 to facilitate long-range correlations between them. Thus to reconcile the slow evolution 185 which characterizes pure thermodynamic processes with the faster one of life’s, an 186 irreverence mechanism is needed to break free from the constraints imposed by 187 thermodynamics while paying obeisance to it, so as to trim phase-space. Now, for the 188 emergence of biological language, the prior presence of co-operative interactions in a set 189 of entities that can define the limits of an environment-coupled system—responding as a 190 whole to external stimuli (Sect.2) at level-I -- need to be associated with a function/s. To 191 that end, inspired by Cairns-Smith’s pre-existing crystal-organization, we look to the 192 signatures of fields on some collectively interacting entities at the inorganic-host-level-I 193 that could have conferred on them the capacity to assist in the advanced stages of 194 complexity, viz. emergence of replicators evolving via natural selection (Hazen 2006). In 195 particular, the advantage of an external H-field cum magnetic nano-particles (MNPs), vis- 196 à-vis say an electric field controlled system of particles, relates to the diamagnetic 197 properties of nano-sized organics ; thus anchoring the latter to mineral colloids responsive 198 to an H-field, is that it can be used as an indirect means to exert control on them (there 199 being associated dielectric properties with both mineral colloids and organic nano- 200 colloids). 201 202 Among possible scenarios, one may consider its potential to give its responsive nano- 203 scale materials 1) a dynamical basis of orientation in a liquid phase enabling formation of 204 aggregates due to dipolar interactions (Taketomi 2011), leading to 2) a response to the 205 external by the generated internal field in the interacting system (Huke and Lücke 2004; 206 Sect.4), whose global evolution would also depend on the susceptibility of its materials to 207 external factors (such as temperature). This quintessential analogue-information system 208 (Palm and Korenivski 2009) seems plausible as a scaffold for the emergence of life as it 209 has potential for cooperative interactions at two levels: a) a colloid component, whose 210 spins (exchange-coupled in MNP lattice) constitute the particle’s composite spin, and b) 211 the dipolar interactions between the components themselves. Indeed, anisotropic dipolar 212 interactions in fluids impinge on fundamentals, such as direction dependence, intrinsic 213 long range nature and susceptibility to external forces (Wei and Patey 1992; Weis et al 214 1992; see Klapp 2005 plus references; Sect.4), and are biologically intriguing (Tavares et 215 al 1999). In ferrofluids (single-domain MNP suspensions in carrier liquids), these can 216 lead to correlations between neighbouring dipoles in growing fractal clusters, wherein to 217 minimize dipolar energy, dipoles prefer to be parallel head-to-tail or antiparallel side-to- 218 side (Pastor-Satorras and Rubí 1995; 1998). In zero-field (for particles with large 219 magnetic moments) dipolar interactions can lead to isotropic fractal aggregates, 220 qualifying them as SOC systems (no external driving). Thus the expected field-induced 221 scaling behaviour was described as the response of this fractal equilibrium system at the 222 critical point to the small external field conjugated to its order parameter (Botet et al 223 2001; see Sect.2). Now, the change from zero-field with diffusion-limited aggregation to 224 a field-driven one in moderate fields is expected to reduce the fractal dimension of the 225 reversible structures (c.f. micro-particles, Domínguez-García and Rubio 2010). The 226 intermediate regime suggests an access to statistical features like scaling on the one hand, 227 as well as controlled mobility on the other, via field-control. These ingredients offer a 228 confined biological-like (level-I) system with potential for feedback effects: its 229 susceptible global-configuration—dictating function-- cannot be determined from 230 properties of its components alone, and it can influence the orientations/dynamics of 231 sterically-coupled organics at guest-level-II (Sect.5). Here, responsive adjustments to 232 changing external influences (via size and magnetic moment of incoming MNPs, 233 reactions or interactions at level-II, fluxes, etc) can affect the network’s capacity to 234 ‘function’ (say transport, Sect.4.6), thus providing a basis for selection of a configuration. 235 The potential to collectively respond to external changes seems an important requirement 236 for a hosting-scaffold (level-I) in view of the penetrating influence of the environment 237 upon a living system whose internal state adjusts to changes in the former. 238 239 Further, the ability of far-from-equilibrium living systems to act as conduits of energy 240 flow equips them with dynamic stability. The construction of their dynamical 241 components/subsystems calls for a scaffold-medium with reversible interactions enabling 242 their interplay with external fluxes, thermal motion, etc. Such a controlled organization 243 with reversible dynamics (Whitesides and Boncheva 2002) —as a starting-point for a 244 cell-like organization-- seems inaccessible to a host medium with irreversible linkages 245 such as rock pores or thermally linked inorganic gels (despite their importance for 246 generating abiogenics, or compatibility with other magnetic/physical effects). Again, in 247 contrast to organics randomly floating within aqueous spaces entrapped in liposomal sacs 248 or rock pores, the suggested flow-reactor-type scenario enables association only of 249 entities actively coupled with the field-controlled system, such as organics bound to 250 mineral-particles, or those interacting with bound organics, etc. (Sect.3.3). To that end the 251 microfluidic system by Park and Kim (2010) seems promising. Furthermore, Ranganath 252 and Glorius (2011) draw attention to the advantages of using externally-controllable 253 super-paramagnetic particles in a range of applications -- from quasi-homogeneous 254 catalytic systems to data storage. Figure 1b depicts the idea that a field-controlled and 255 dynamically stable inorganic modular organization (c.f. Cairns-Smith 1985) can i) 256 support the gradual evolution of organic mixtures at guest-level-II, ii) be compatible with 257 the simultaneous emergence of different kinds of organic networks/autocatalytic 258 subsystems (c.f. Gánti’s (2003) 3 sub-systems), iii) simultaneously affect any coupled 259 subsystems and thus hasten their mutual cooperative interactions, via an SOC mechanism , 260 thanks to the influence of the environment on its own d.o.f.s, and iv) by virtue of its 261 capacity for some primitive functions, provide a selection basis towards its own 262 ‘takeover’ by superiorly functioning organic networks. Note that this crucial role 263 envisaged for an inorganic functional scaffold only concerns the initial stages of life’s 264 emergence, for providing a feedback circuit between levels I and II till both became 265 organic-based. 266 Metabolic-networks

Replicating templates Increasing complexity

Reaction-diffusion patterns

(a) (b) 267 268 269 Figure 1 270 271 To get an intuitive feel for the organizing power of a field, think of system-components 272 as compasses detecting/responding to magnetic field lines, or iron filings showing the 273 lines of force from a bar magnet. Similarly liquid-dispersed magnetic nano-particles form 274 chains of north-to-south, joining together end-to-end, while adjacent strings show a 275 repelling property. In a similarly polarized ferrofluid 276 (http://en.mobile.wikipedia.org/wiki/File:Ferrofluid_poles.jpg ) this particle alignment effect is spread 277 uniformly throughout the liquid medium and a sufficient field for overcoming 278 gravity/surface tension can make spikes appear (e.g. see Peter Terren’s website 279 http://tesladownunder.com/Ferrofluid.htm ). In fact, the remarkable similarity of magnetic/electric fields 280 on MNP/thread suspensions, respectively, to the mitotic spindle, led Rosenberg and 281 coworkers (1965) to study the effect of fields on cell division and related applications. 282 Also, the dimensions of a cell~ 10 -100 micrometer; protein ~5-50 nm; gene~2nm wide 283 and 10 -100nm long (Pankhurst et al 2003), show that MNPs have the same length scale 284 as biomolecules, thus making it possible to apply magnetic-field induced clustering and 285 cell signaling using these tiny magnets as ligands (Mannix et al 2008; see also Chen 286 2008), and also enhance the potential of field-effects in origins-of-life research. The 287 crucial role of fields in biology today underlying cooperative effects (see Ho 1997 and 288 ref), also provides a natural motivation to look for coherent influences in the origins of 289 life that could have caused cooperative interactions . 290 291 In this review, Sect.2 considers the implications of SOC in life’s emergence, after a brief 292 look at biological-systems and SOC. Sect.3 studies Cairns-Smith’s “crystal-scaffold” 293 organization using an LC-medium, and the potential of a soft-scaffold for assisting 294 bottom-up approaches via kinetic aspects. Towards a ‘boot-strapping’ scenario, we 295 briefly look at field-induced dynamical structures in Sect.4 to see how field-control can 296 cause confinement of particles, influence their global configuration, and render them as 297 carriers for transferring heat and electrons. Sect.5 studies how these controlled-systems 298 could have caused cooperative transitions in organic-matter. Sect.6 briefly considers 299 fractal structures and their implications for harnessing gradients, and studies the 300 hydrothermal mound scenario with potential for forming such structures, before 301 conclusions in Sect.7. 302 303 2 Living systems and SOC; implications of SOC in life’s emergence 304 305 2.1 Living systems and SOC 306 Biological systems are self-organizing systems with a globally coherent pattern emerging 307 spontaneously, thanks to the cooperative local interactions of its components. Important 308 universal facets include: 1) distributed control , with all elements functioning as 309 independent units in parallel, e.g. heterarchy in an ant colony (Dréo and Siarry 2004); 2) 310 controlled work-cycles of nano-machine components ; for example, motors require a slow 311 input from a non-equilibrium source (homogeneous) plus rectified thermal fluctuations, 312 thanks to the asymmetric nature of their surfaces appropriate for ratchet dynamics 313 (Astumian and Derenyi 1998; Astumian and Hangii 2002); 3) controlled global dynamics 314 of the system undergoing slow and adaptive alterations in response to environmental 315 fluctuations; 4) chirality and polar asymmetry of building blocks for asymmetric 316 dynamics; and 5) fractal (nested) nature of organization (Ho 1997), for components to 317 locally operate close-to-equilibrium (see point 2) with optimal efficiency despite staying 318 globally far-from-equilibrium. 319 A similar fluctuation-driven formation of order from disorder is a familiar phenomenon 320 in equilibrium systems undergoing phase transitions (see Box-I)--a typical form of 321 spontaneous symmetry breaking. Note that potential energy is an integrated effect of 322 interactions of specific arrangements (e.g. parallel/anti-parallel spins), signifying order, 323 unlike fluctuations that characterize disorder. And spontaneous symmetry-breaking 324 means that despite the system’s equations of motion being symmetrical, the instability in 325 the internal chemistry of its components, causes a loss of homogeneity/symmetry to the 326 system’s state (Anderson and Stein 1985). Transitory self-organized patterns are also 327 seen in turbulent thermodynamic systems far-from-equilibrium, e.g. convection but they 328 do not match those of robust living systems that exhibit stability and control at each point 329 of their dynamics, despite dissipating energy and creating entropy to maintain their 330 structure (Anderson and Stein 1985). Again, in vortices, typically macroscopic 331 perturbations or higher-level structures do not modify the (internal) structure of the 332 molecular components, unlike the bi-directional informational flows between different 333 levels of bio-organization (Hartwell et al 1999). On the other hand, the fractal patterns in 334 diffusion-limited aggregation (DLA) processes are somewhat reminiscent of structural 335 complexities of their bio-counterparts, especially in the transporting role of diffusion 336 (Witten and Sander 1981). 337 338 The analogy to slowly evolving living systems becomes clearer for certain slowly driven 339 non-equilibrium systems that can “self-organize” into a robust stationary state with a 340 scale-invariant macroscopic behaviour, owing to dissipative transport processes 341 associated with a critical variable (Bak et al 1987; 1988). This phenomenon--dubbed as 342 self-organized criticality (SOC) —shares some commonalities with the equilibrium 343 concept of second order phase transition (see Box-I), usually associated with scale- 344 invariance, maintained by fine-tuning with a parameter like temperature (T). But unlike 345 its equilibrium counterpart, the critical state is an attractor of the dynamics in SOC 346 requiring a separation of time-scales between external driving and internal relaxation (see 347 Bonachela Fajardo 2008). Rather paradoxically, by providing a condition for toppling, 348 the presence of a threshold offers a condition for stability. With a zero threshold, the 349 component sites would be always in an active state, with the system perpetually 350 undergoing avalanches involving many (interacting) sites but little stored energy. At the 351 other extreme (infinite threshold) each site would store the energy received, without 352 interactions or transport of energy; thus making the system undergo unitary sized 353 avalanches. But a non-trivial threshold, plus a conservative rule for redistribution of 354 energy, can lead to correlations between the sites, thus making for a spatially extended 355 response to an external local perturbation. Thanks to closely spaced metastable states, the 356 system can evolve by hopping from one to the other in response to perturbation-triggered 357 avalanches where instantaneous relaxations involving the entire system occur (Bonachela 358 Fajardo 2008). 359 360 Box-I 361 362 363 Phase transitions; order parameter 364 365 • Phase transitions were classified by Eherenfest as: 366 a) First order if there is a discontinuity in the first derivative of the free energy, in the form of 367 a finite energy shift where the order parameter exhibits a discontinuous jump at the transition 368 temperature T with an associated release (or absorption) of latent heat, e.g. as in 369 370 crystallization 371 b) Second order if the first derivatives of the free energy—namely the entropy and the 372 magnetization --are continuous (no latent heat) at the critical point, but the second derivatives 373 of the free energy-- namely the specific heat as well as the magnetic susceptibility —show a 374 discontinuity in the form of a divergence (or singularity), as in magnetization of a 375 376 ferromagnet. 377 • It was Landau who first introduced a quantitative measure of order appearing at the phase 378 transition, through his definition of an “ order parameter ” (valid at or near equilibrium). It 379 signifies the range over which fluctuations in one region of a system could be affected by 380 381 those in another. In the case of a ferromagnet, the order parameter is magnetization (M). 382 383 384 385 This kind of dynamics steadily goads the system towards a state in which the 386 outgoing energy balances the incoming one on average, leading to a scale-free behavior. 387 Unfortunately its meaning remains restricted, by limited consensus (see Halley and 388 Winkler 2008; Turcotte 2001), to the sand-pile model (Bak et al 1987; 1988) whose 389 principal feature is that the (last) `fractal pile'-- symbolizing the critical state -- gets 390 upset by even the addition of an extra grain of sand on top of it due to the local slope of 391 the pile crossing a threshold. This can lead to the toppling of only two grains to an 392 avalanche affecting the entire pile surface with sand-loss at the boundaries, thereby 393 maintaining the stationary critical state (Adami 1995; Bonachela Fajardo 2008; Dickman 394 et al 2000). To generalize to similar phenomena for greater universality, explanations for 395 such “unguided” critical dynamics have been proposed via their implicit association with 396 a tuning parameter (Dickman et al 1998; Sornette et al 1995) like in equilibrium critical 397 phenomena. In an absorbing-state (AS) phase transition, a tuning parameter--the particle 398 density -- determines whether the system is in an active phase (changing in time) or in an 399 inactive phase (stuck in one configuration). The order parameter of these transitions is the 400 density of sites about to topple, called the activity (Dickman et al 1998). The coupling 401 between order and control parameters helps attract the control parameter to its critical 402 value and brings about the phase transition, as well as shows the possibility of a role- 403 reversal (Sornette et al 1995). Thus, notwithstanding its lack of a general formalism, SOC 404 could still provide some insights into the complex behaviour of evolving biological 405 systems. This is since the susceptibility of the organism as a whole (changes in functional 406 patterns manifest in nucleic acid sequence space) to the environment controlling its 407 evolution, betrays an intrinsic memory mechanism, enabling it to sense and respond to its 408 external conditions by changing its internal configuration —via an analogous coupling of 409 control and order parameters (Sect.1). To that end it uses a diversity of closely-spaced 410 (metastable) states , resulting from co-operative interactions between many d.o.f.s —all 411 typical ingredients of SOC. 412 413 2.2 Implications of SOC in life’s emergence 414 415 It is interesting to consider a similar control/order parameter coupling-scenario between 416 an environment and its system to understand evolution by natural selection or life’s 417 emergence. Indeed, for insights into the major transitions in evolution, (Maynard Smith 418 and Szathmáry (1995)), leading for instance to improved functionality in an organism, 419 another study (Suki 2012) proposes that phase transitions in the network structure 420 associated with that function can facilitate the transition to improved functions. Now, 421 computer simulations have provided numerous insights (Kauffman 1993; Kauffman et al 422 2004; see Gershenson 2010) into the effect of lower-scale network parameters on their 423 higher-level dynamical properties, which would impact different global aspects 424 (robustness, evolvability, adaptability). And, network features like modularity, 425 redundancy, and scale-free topology can help the system exploit noise (Fernández and 426 Solé 2004)--an asset for functioning in a robust manner despite fluctuations. Next, 427 Gershenson (2010) suggests that although criticality may be present even without shifting 428 the phase transition or broadening its regime by tinkering with different network features, 429 these properties can guide the system and promote criticality. Furthermore, natural 430 selection may well have exploited such methods to guide the self-organization of genetic 431 regulatory networks towards the critical regime. But this also brings up the intriguing 432 possibility that such networks had themselves emerged via similar tinkering of precedent 433 ones—in a continuous gradual process. More explicitly, we ask if the computing power 434 of organisms that is inherent in the adaptive process (Hartwell et al 1999) could be 435 extrapolated backwards to a rudimentary information processing system in the pre-biotic 436 era that may have guided the evolution of random chemical networks. Indeed Cairns- 437 Smith’s (2008) abstraction of control-organization from these computing systems frees 438 them from the material details and helps to extrapolate the LUCA back in time. Here, 439 starting from the pre-biotic era, transitions (c.f. Suki 2012) between information- 440 processing machinery by changing materials/architecture/mechanisms--, in response to 441 environment fluctuations in an SOC scenario-- require functions associated with the 442 ancestor to be fulfilled by its replacements. 443 444 3 Liquid crystals (LCs); Cairns-Smith’s scaffold paradigm; and bottom-up approaches. 445 446 3.1 LC medium as a scaffold-organization 447 Complex bio-molecules—important components of the control-network—are capable of 448 large response-effects a la de Gennes (2005), typical of soft-matter, thanks to correlated 449 motions of their constituent atoms. They display liquid crystalline phases both in vivo and 450 in vitro . The relevance of an LC medium to biology (see Table–I, adapted from Bisoyi 451 and Kumar 2010), owes it to a feature of cooperativity that facilitates responses to 452 external stimuli (apart from control and stability), but one which is missing in a random 453 mixture of its constituent building blocks (amino-acids, nucleotides, etc.). Besides its 454 intrinsic properties, it can act as an influential host medium for the evolution of its 455 embedded materials by controlling their orientation, helping assembly, and transferring 456 its own sensitivity to external-fields due to steric-coupling (point 6, Table 1; Sect.5.1), 457 and thus makes it easier to understand Cairns-Smith’s (2008) scaffold paradigm. As non- 458 equilibrium states are stable when they act as energy carriers, in the absence of any new 459 functional structures appearing, this medium of cooperatively acting components can 460 offer its own (rudimentary) capacity to act as an energy conduit. Conversely, it can be 461 dispensed with in favour of new emerging structures with superior functions. Thus such 462 dynamic stability ensuing from cooperativity in a medium would have provided time for 463 the interactions between its randomly engendered materials to lead to the gradual 464 appearance of constructs of increasingly higher specificity and lower connectivity (c.f. 465 Kauffman 1969), that could range from structures to complex spatio-temporal patterns, 466 capable of canalizing energy more efficiently. This gels with Langton’s (1990) emphasis 467 on the vital dependence of complex computations requiring diverging correlations in time 468 (for memory), and length (for communications), on phase transitions , in the context of 469 life’s emergence, by insisting on the primitive functions required for computation, viz., 470 the transmission, storage, and modification of information, so that it can spontaneously 471 emerge as an important factor in the dynamics of a system. 472 473 474 475 476 477 478 479 480 481 482 483 Table –I: The importance of being liquid crystalline. 1. Capacity to combine order and mobility underlies its Hamley 2010 crucial role in self-organization and structure formation in biology. 2. Important biopolymers e.g. lipids, proteins, Hamley 2010 carbohydrates and nucleic acids display liquid crystalline phases both in vivo and in vitro . 3. Like cells LCs can amplify and transmit information Goodby, et al 2008 4. Like cells, they can dynamically respond to a large Demus et al 1998 number of external stimuli e.g. changing chemical concentration, temperature, light, electric, magnetic fields and other environmental changes 5. Liquid crystals have potential for electron, ion, Kato et al 2006 molecular transport, besides sensory, catalytic, optical properties 6. Control effects: A scaffold medium --as a ‘precursor’ Bisoyi and Kumar 2011 template a la host-level-I --can exert its influence upon its dispersed materials—corresponding to guest- level-II (see text). 6a Far from inducing distortions various nano-materials Hegmann et al 2007 dispersed in LC media have been observed to enhance their physical properties. 6b The anisotropic nature and tenability of LC media Kumar 2007 ; Hegmann et can facilitate the alignment and self-assembly of al 2007 nano-materials randomly dispersed within. 6c Thanks to the sensitivity of LC media to small Bisoyi and Kumar 2011 external stimuli, the latter can thereby influence the dispersed materials that are sterically coupled to the host’s dynamics . 484 485 486 3.2 The scaffold as a controlled cooperative organization 487 488 As mentioned above, rather than suggesting the spontaneous emergence of an entire 489 language from random processes alone, the scaffold-paradigm offers a context-laden pre- 490 existing control-organization , associated with bio-like evolution. It provides an 491 environment-responsive functional inorganic organization-- level-I-- to host/guide the 492 (irreversible) evolution of random organic reactions/assemblies-- level-II. Conceptually, 493 assistance from a controlled organization, via crystal-vibrations (Cairns-Smith 2008), 494 would have elevated the status of a proto-metabolic cycle—associated with a 495 thermodynamic motivation—to that of a function . The gradual ‘takeover’ of level-I by 496 organics would have led to today’s environment-coupled 2-tier-system comprising the 497 control-network (level-I) feedback-coupled with the metabolic-network (level-II), 498 supplying energy and building blocks. Note that in contrast to living systems-- whose 499 ordering source comes from their dissipation of energy (closure; Shapiro 2007), a 500 scaffold awaiting ‘takeover’ is not constrained to follow this pattern. But it does need a 501 sustained source for its ordering and access to non-eq sources. To that end, bottom-up 502 approaches indicate how autocatalytic cycles, e.g. reverse citric-acid cycle (Morowitz et 503 al 2000), may have served as energy channels releasing disequilibrium stresses, besides 504 providing building blocks for the control-network (Copley et al 2005), although they 505 require mechanisms providing kinetic assistance and pruning of side reactions . Today, 506 regulated enzymes lower activation energy barriers by controlling the orientations of the 507 reactants. True, it is hard to imagine a corresponding variety of enzyme-like specifically- 508 binding surfaces via a crystalline matrix (see Orgel’s (2000) perplexity at 509 Wachtershauser’s conclusion). Nevertheless, the effect eventually caused by the different 510 enzymes, viz. of trimming the phase-space of the reacting species (level-II), could have 511 been achieved via the association of some pre-existing control organization --level-I-- 512 with the random pre-biotic reactions. 513 514 3.3 How “cooperativity-first” could complement bottom-up approaches 515 516 Approaches considering cooperative phase-transitions in random networks for life’s 517 emergence (Bollobas and Rasmussen 1989; Dyson 1982; Kauffman 1986; see Hordijk et 518 al 2010) may have overlooked the possibility of such a ‘top-down’ pre-existing kinetic 519 principle helping its onset. These consider the emergence of a non-genomic replicator by 520 random drift through autocatalytic closure of simple catalytic molecules that could have 521 preceded template-replicators. Now, in looking for the “ultimate ancestors of modern 522 enzymes”, Dyson indeed considers the possible role of clay crystals or iron sulphide 523 membranes, but merely as passively confining surfaces, which obscures their possible 524 impact on the probabilities of a gradual transition from a random collection of catalytic 525 units to a co-operative population, say via the mean-field approximation (c.f., Curie- 526 Weiss model of a ferromagnet), since the population of molecules slowly diffuses over 527 the transition barrier. Nonetheless, taking inspiration from Dyson’s (1999) ‘cells-first’ 528 model, we explore the possibility of a directed way to more structured quasi-stationary 529 states --“possibly with active biochemical cycles and higher rates of metabolism ”-- from 530 within a random and disorganized population of molecules, “ in an assemblage of many 531 droplets existing for a long time ”. As mentioned (Sect.1), the intermediate regime 532 between diffusion-limited and field-driven aggregation of anisotropic colloids seems to 533 have potential to access the features of scaling and controlled mobility in disordered 534 liquid medium. Thus, binding to these colloids would have caused a drastic reduction in 535 the phase space available to the reacting organics towards bringing about such a transition 536 thanks to the invisibility of H-fields to organics (poor diamagnetic susceptibility). It is 537 logical to suppose that magnetic-interactions would restrict the possible orientations of 538 the organic-bound mineral-particle; this physically rules out some interactions/reactions, 539 while kinetically assisting the feasible ones thanks to the flexibility of the magnetic 540 ‘template-surfaces’ (Ommering 2010; Baudry et al 2006; Sect.5). 541 542 As a scaffold hosting random reactions, the field-organized system of nano-particles has 543 potential to fulfill the requirements of distributed-control and kinetic assistance in top- 544 down and bottom-up approaches, respectively, to the origins of life (c.f. Sun 2007 ). And 545 as the interplay of order and disorder at all scales is also feasible via magnetic d.o.f.s, the 546 emergence of dissipative living systems (c.f. Nicolis and Prigogine 1977) is postulated to 547 have started from such a scaffold-organization dissipating (coherent) field energy for its 548 formation. Albeit close-to equilibrium initially, over time it got slowly pushed further and 549 further away from equilibrium upon gradual “takeover” by (its selected) organic-based 550 complex components, with an analogous capacity of dissipating homogeneous sources of 551 energy for sustaining their stable and “mutually interdependent dynamics” (Cairns-Smith 552 2008). This is plausible since the entropy of the super-system---the controlled system plus 553 its environment—would then increase at a faster rate. This field-controlled system offers 554 a mechanism for i) confining adsorbed organics, ii) giving access to diffusing-in 555 ‘food’/materials, iii) permitting generated ‘wastes’ to diffuse out, hence acts like a flow 556 reactor with analogy to Dyson’s pre-biotic “cell”. 557 558 559 Sec.4 Field-control assisted functioning scaffold organization 560 561 From among a variety of magnetic effects having implications for life’s emergence 562 the chief emphasis will be on reversible field-induced aggregates to simulate an evolving 563 biosystem. That such aggregates can form (Taketomi 2011) encourages the assumption of 564 their presence in pre-biotic locales, although here one expects greater system-complexity 565 than in the following studies, since there could have been no control on parameters 566 (particle sizes, composition, etc.). But a chief concern is the absence of steric-effects in 567 surface-modified synthetic ferrofluids, to avoid short-range attractive forces. This leaves 568 unaltered action-at-a-distance effects like co-localization of particle-anchored organics, 569 but could affect the scenario of a field-controlled scaffold. Nevertheless, the mutual 570 interplay of magnetic-attraction and charge-repulsion —as in framboid formation 571 (Sect.6)—shows a way to register short-range repulsion between particles. 572 573 4.1 Brief background: Thanks to thermal fluctuations, magnetic single-domain nano- 574 particles --key players in this scenario--are disoriented at room temperature. A moderate 575 H-field suffices to break the rotational symmetry of such nano- particles, by imposing a 576 directional order against their thermal fluctuations, see Figure 2, taken from Chantrell 577 (1982; see also Klokkenburg et al 2006; Richardi et al 2008). Li et al (2007) describe 578 field-induced aggregates as a phase separation of a particle-concentrated phase from a 579 dilute one. These (close-to-equilibrium) ordered structures --requiring about tens of milli- 580 Tesla fields for their formation-- are dissipative in nature, breaking up when the field is 581 switched off. They are also amenable to control parameters like field strength, sweep rate, 582 concentration, strip- width and strip-thickness. Thus, with the external H- field exceeding 583 a critical value, the original magnetic nanoparticles started to agglomerate into magnetic 584 columns and, with its further increase, formed several levels of ordered structures (Yang 585 et al 2003). As checked by small angle neutron scattering, chain size also depends on the 586 strength of inter-particle interactions (Barrett et al 2011). 587 588 589 Figure 2 590 591 592 An important property of magnetic nano-particles is that of anisotropy (see the classical 593 Stoner-Wohlfarth (1948) model); so that the applied field helps the hysteretic rotation of 594 the magnetization to jump over the magnetic-anisotropy barrier. Next, in general, the 595 relaxation of a single-domain nano-particle can take place via two distinct mechanisms: 596 1) Brownian- the individual magnetic moments, are rigidly fixed against the nano- 597 particle’s crystal lattice so that the particle rotates as a whole; 2) Neel- the individual 598 magnetic moments rotate within the (fixed) nanoparticle. But this would also depend on 599 its physical state. Thus, taking particles whose magnetization is not completely frozen 600 (Neel relaxation time much faster than their measurement time), and dispersing them in a 601 liquid medium would give the colloidal particle’s magnetization both Neel and Brownian 602 modes of relaxation. The latter-- proportional to the crystal volume-- characterizes the 603 viscous rotation of the entire particle (irrelevant for dry powders), unlike the former (an 604 exponential function of the volume). Therefore the Brownian mode for return to 605 equilibrium becomes the dominant process for large single-domain particles suspended in 606 a liquid medium. Its characteristic time scale can be studied via ac susceptibility; thus an 607 increase in hydrodynamic radius, such as upon binding to organic ligand --e.g. biotin to 608 avidin-coated nanoparticle (Chung et al 2004)— resulted in a shift in the magnetic 609 susceptibility peak vs frequency curve at 210Hz to 120 Hz. Importantly, the degree of 610 inter-particle-interactions (c.f. Mørup et al 2010) can significantly affect this relaxation 611 mode (relevant for further diffusing-in particles into an aggregate). Recall also that over 612 and above the orienting effect of a field, a further enhancement of the magneto-viscous 613 effect (velocity-gradient caused rotation of suspended particles, hindered by field applied 614 perpendicular to sheer flow) was attributed to structure formation (Pop and Odenbach 615 2006). Furthermore, since the dipolar interaction between two neighbouring particles 616 increases with decrease in intercrystal distance, the particle’s aggregation-state should 617 have an effect on the Neel relaxation, due to the dipolar inter-crystal coupling aspect of 618 the anisotropy (Laurent et al 2008). 619 620 4.2 Analog for confinement: Field-induced (dipolar) interactions offer a ready mechanism 621 for confinement of MNPs by overcoming thermal fluctuations, see Figure 2 (reproduced 622 from Chantrell 1982). The dynamical aggregates, whose components interact via weak 623 reversible complementary dipolar forces, are analogous to living systems with distributed 624 control and whose components dissipate homogeneous sources of energy. Other than 625 such magnetic field induced aggregation—likely a second-order phase-transition 626 (Taketomi 2011)-- magnetic dispersions can also be ordered by other coherent sources, 627 e.g. light (Köhler and Hoffmann 2003), and electric field (Riley et al 2002; Duan et al 628 2001). This expands the scope of field-control for access to scaffolds that could have 629 been present in a variety of pre-biotic environments. Now, agglomeration of H-field 630 aligned nano-particles-- dispersed in a fluid-- leads naturally to a bottom-up assembly 631 compliant to top-down control (see Chantrell 1982; Rosensweig 1985), wherein 632 the spread of the aggregate is defined by the field’s zone of influence (~ inverse square 633 law). An equilibrium state is reached when the number of particles leaving the aggregate 634 balances those getting attached (Fang et al 2008). Next, we suggest that in an open 635 system, the possibility of further particles diffusing into it and aligning to the assembly 636 “layers” would provide an analog for “replication”/growth. 637 638 4.3 Correspondence to machine-like components 639 That bio-systems choose to function near the cooperative transitions of their myriad 640 different bio-molecules also gels with ‘takeover’ from pre-existing modules functioning 641 primitively via collective effects. Bio-molecular machines are many-atom containing 642 molecules whose dynamics seems to be governed by the fluctuation-dissipation theorem 643 (FDT) (Bustamante et al 2005). Their cooperative atomic motions enable reversible 644 switching between conformational states for work cycles. This seems analogous to the 645 capacity of exchange-coupled magnetic moments in an MNP lattice to change their spin 646 orientation in response to local variations of the external H-field (via Zeeman effect). 647 648 4.3.1 Diffusion aided processes: Imagine further incoming MNPs, diffusing into their 649 field-induced aggregate of MNPs in an aqueous medium (see Figure 2b; c.f. work cycles 650 of a molecular motor moving on a template). Now as a dipole (depicted in blue in Fig.3) 651 diffusively migrates through the ‘layers’ of the aggregate (depicted in black), in addition 652 to the H-field and bath fluctuations, its orientational state is influenced by the local H- 653 field of its “template” partners forming the aggregate. We also imagine a gentle H-field 654 gradient --stemming from (inhomogeneous) magnetic rocks (Mitra-Delmotte and Mitra 655 2010a)--that provides both detailed-balance-breaking non-equilibrium as well as 656 asymmetry, to a diffusing magnetic dipole undergoing infinitesimal spin-alignment 657 changes. The gentle gradient-driven diffusion of the migrating dipole (c.f. thermophoresis 658 Duhr and Braun 2006) would thus be periodically perturbed by local H-fields of its 659 ‘template’-partners, leading to alternating low and high-‘template’-affinity states due to 660 the dipole’s magnetic d.o.f., rather analogous to the isothermal release/binding cycles in 661 the priming/operative phases of the molecular machine (Schneider 1991). Within a 662 common FDT framework for asymmetric movements, these changes would be similarly 663 facilitated by thermal excitations from bath, with rectification by either the gentle H-field 664 gradient or the fields of its local ‘template’-partners (see Figure 3 legend). Note also that 665 binding to non-magnetic ligands (e.g. organics) would increase the net potential energy 666 barrier of the particles for interacting with their ‘template’-partners, compared to their 667 ligand-free counterparts. Hence, greater diffusive exploration of the organic-bound 668 particles leads to a bio-molecular motor-like scenario, while the entrapment of the 669 isotropically unshielded ones into an expanding network of dipolar interactions has the 670 appearance of growth phenomena. 671

672 673 Figure 3 674 675 Now, a magnetic ratchet seems promising for the controlled directed transport of 676 micrometer-sized colloids at the solid-liquid interface, as displayed by bio-nano- 677 machines using the ingredients of non-equilibrium source, asymmetry, and a periodically 678 varying potential in space/time. Tierno et al (2008) achieved this on the surface of a 679 ferrite garnet film with a magnetic domain pattern forming a periodic array of stripes with 680 magnetization alternating up and down, and applying time-dependent external magnetic 681 field pulses. Their video-microscopy tracked experiments show the transversal motion of 682 particles on the hard film providing the local ‘template’ fields (Tierno et al 2010). This 683 seems to have potential for being scaled down to nanometer-sized heterogeneities 684 towards a magnetic shift register. Further, tunable heterogeneous field-variations on the 685 nano-scale have not only been used for the controlled movement of aqueous phase 686 dispersed MNPs, but also for their separation based on size of the particles (Tierno et al 687 2008 ). The fact that the latter could be used to separate complementary oligonucleotides 688 via a “hot zone” for melting the DNA strands, shows their compatibility with the energy- 689 scales required for controlled biomolecular interactions, and suggests their relevance for 690 envisaged scaffold effects. Also, an interplay of magnetic with micro-convection (Mast 691 and Braun 2010) effects could have potential to cause periodic binding and de-binding 692 between interacting particles. 693 694 A plausible picture as to how organics could have gradually ‘taken over’ from such 695 dynamics is revealed via a mechanism like the autonomous motion of Janus particles 696 whose surfaces are designed to have asymmetric chemical properties (see Baraban et al 697 2012). One strategy is the catalytic action at one end of the particle that can generate the 698 generation of an anisotropic chemical gradient across its surface, and this self-generated 699 force drives the particle’s movement through a liquid medium. And initially during the 700 transition, an external field’s orienting effect may well have guided such directed 701 migration (as in Kline 2005; Gregori et al 2010 ) before other control mechanisms such as 702 today’s chirality-based ones got installed. 703 704 It is important that the size scales of the non-magnetic colloids be kept in mind, when 705 assembling bio-molecules using magnetic effects. For instance, in a magnetizable fluid, 706 large non-magnetic colloids ~ 100nm have been shown to be pulled towards the lower 707 end of the field-gradient (exactly opposite to their magnetic counterparts) called negative 708 magnetophoresis (Halverson 2008; Yellen et al 2005)—a method used for their 709 manipulation and assembly by magnetic fields. This volume effect is likely to be 710 negligible for organic ligands, like small peptides considered here; for comparison, a 711 large 20kDa peptide (~170 amino-acids) has an R min of 1.78nm (Erickson 2009). 712 713 4.3.2 Magneto-structural transitions: Now, secondary effects of magnetism in a substance 714 are caused by couplings between its different physical properties: magneto-caloric, 715 magneto-electric, magneto-optic, magneto-striction (De Lacheisserie et al 2005), 716 analogously to similarly coupled d.o.f.s (thermal, elastic, electric, etc) of complex 717 biomolecules (Cope 1975). This raises the possibility that similar transitions in magnetic 718 mineral particles (Hemberger et al 2006) comprising field-structured aggregates had 719 assisted some work-cycles, especially since surface-to-volume effects become sizeable at 720 the nanoscale. For example, in the priming step in molecular machine functioning 721 (Schneider 1991), energy is supplied by a field-like (homogeneous) source, typically 722 ATP, plus thermal motions captured from the bath. This is followed by the operating 723 phase wherein dissipative ordering for information gain –recognizing a surface and 724 reducing its conformational uncertainty—and release of entropy to the bath, takes place. 725 The energy-shift via entropy reduction is effectively a first-order phase-transition . In the 726 corresponding magnetic scenario for directed transport, an accompanying magneto- 727 caloric effect can permit an interchange between system-entropy and bath temperature 728 under isothermal conditions; also a magnetic field-controlled nano-particle assembly 729 mimics recognition-based binding interactions between particle surfaces. Again similar to 730 spatial field inhomogeneities causing motor-like effects, temporal field-variations, can 731 cause binding/release cycles between interacting MNPs, analogously to complementary 732 bio-surfaces. 733 Note that heat released from a reaction, can alter the magnetization of the particles, vide 734 Neel’s (1949) study. Further, two analogies of magnetic mechanisms to bio-molecular 735 ones are intriguing: 1) the activation energy of a substrate in a chemical reaction is 736 similar to the anisotropic energy hump of a single domain magnetic nano-particle, 737 flipping from one easy direction to the other; and 2) the interconnections between 738 magnetic elastic and thermal properties in magnetic shape memory materials are rather 739 reminiscent of enzyme dynamics. For example, a change in the material’s magnetization 740 by changing an external H-field can not only bring about its deformation (magnetoelastic 741 effect) but also an entropy variation (magnetocaloric); likewise a deformation due to an 742 applied stress, can cause both a magnetization and an entropy change (Giudici 2009; c.f. 743 martensitic-like transformations in cylindrical protein crystals, Olson and Hartman 1982). 744 Alternatively, similar shape-memory effects could also have been effectuated by the 745 diffusive entry of small thermo-responsive polymers, and subsequent binding to 746 magnetically heatable colloids in the scaffolds (Mohr et al 2006; Schmidt 2007; Zheng et 747 al 2009). 748 749 4.4 Global evolution of aggregates: The field-induced assembly of dispersed nano- 750 particles falls under the general category of granular systems with complex interactions 751 (Aranson and Tsimring 2006), with weak magnetic dipolar interactions providing a 752 global correlation mechanism. The analogy between electric dipolar interaction-based 753 organization in living systems and magnetic dipole interactions in a reversible aggregate 754 (Taketomi 2011) wherein the latter can be influenced by an externally applied H-field, 755 makes them interesting as scaffold-systems a la Cairns-Smith. Ideally, a completely 756 reversible system can capture the interplay between several competing factors, such as 757 magnetic dipolar interactions, thermal fluctuations, screening effects of the medium 758 (Pastor-Satorras and Rubi 2000). Intriguingly, the complex effects of the long-range 759 magnetic dipolar interaction (Huke and Lücke 2004 plus references) —itself dependent 760 on the macroscopic distribution of the particles-- leads to feedback between the external 761 and internally generated fields. This scenario seems to be analogous to the sensitivity of 762 the internal state of living systems to external influences. Although we are unaware of 763 experiments that correspond exactly to these speculations, nevertheless, some insights 764 can be had from the seminal associative memory model of Hopfield extrapolating from 765 physical systems to spontaneous bio-computation as a collective property of 766 autonomously functioning units (Hopfield 1982). Also, the simulations (Ban and 767 Korenivski 2006, Palm and Korenivski 2009) employ a ferrofluid -based associative 768 neural network for pattern storage, wherein inhomogeneous H-fields influence dipole- 769 dipole interactions in the network, with the respective transition probabilities satisfying 770 detailed balance. 771 772 In this context, Brevik (2001) first used a life-like system of magnetic floating objects 773 plus thermocycler, as instantiation of uncertainty reduction in producing complementary 774 sequences, and for relating thermodynamics to information—defined as the shared 775 entropy (via patterns) between two independent structures—in living systems. Even 776 without catalysis, spontaneous interactions between monomers bound to a polymer 777 resulted in complementary-string formation in response to environmental temperature 778 fluctuations, thereby demonstrating the self-organization of template-replicating 779 constructs towards Darwinian evolution. Although he used macroscopic objects, this 780 scenario is down-sizeable. 781 782 783 4.5 Far-from-equilibrium regime: Organic bonds (at level-II) could prevent dissociation 784 of field-induced aggregates and enable their drift to locations providing non-equilibrium 785 conditions (c.f. Goubalt et al 2003). For in contrast to static-field induced equilibrium- 786 like clusters, alternating fields can provide interesting configurations, e.g. dynamical self- 787 healing membranes (Osterman et al 2009), and swimmers (Dreyfus et al 2005). Further, 788 spinning ferromagnetic disks at the liquid-air interface assembled into patterns due to 789 interplay of repulsive hydrodynamic (vortex-vortex) and attractive magnetic (coupling to 790 average field of rotating external bar-magnet) interactions (Grzybowski et al 2000; 2009; 791 Whitesides and Grzybowski 2002). Again, dynamic elongated self-assembled structures-- 792 suspended at the liquid-air interface-- emerged in a certain range of excitation parameters 793 owing to competition between magnetic and hydrodynamic forces. Furthermore, self- 794 propelled “swimmers” formed upon spontaneous symmetry breaking of the self-induced 795 hydrodynamic flows (Snezkho 2011). 796 797 Now, the formation of dissipative organic assemblies at level-II requires an energy 798 source, which a scaffold with a capacity to store (coherent) energy can support. Indeed, 799 field-tunable aggregates can store polarized (retrievable) light, its wavelength being 800 determined via the refractive index of microcavities formed by the aligned spheres (Patel 801 and Mehta 2011). 802 803 4.6 Transfer of heat; electron transmission 804 Tunable dipole-dipole interactions between MNPs -- via external field strength and its 805 orientation, etc. -- can influence heat percolation through the network. Recent results 806 (Philip et al 2008; Shima et al 2009) show a 3-fold enhancement of thermal conductivity 807 of a ferrofluid over the base fluid’s, thus suggesting an efficient percolation mechanism 808 via field-induced aggregation of 3-10nm magnetic particles. Very large conductivity is 809 observed with parallel fields versus low values for the perpendicular mode. Similarly, a 810 field-induced magnetic dipolar network, can also transport (spin-polarized tunneling) 811 electrons (Pu et al 2007). The possibility of percolation of heat and spin-transmission of 812 electrons-- via dipolar interactions-- in a field-induced MNP-network, hosting reactions 813 makes it interesting to consider feedback effects. A reaction at level-II could impact the 814 MNP-network configuration at level-I, say by releasing heat and increasing local 815 temperature or altering the redox state and therefore the magnetic moment of the hosting 816 particle/s (at level-I) (see supplementary information). 817 818 Now, thermionic emission via the Richardson effect could have provided single electrons 819 (c.f. pairs from redox reactions) to inorganic-scaffolds, which seems relevant in view of 820 the possible role of electron-bifurcation via crossed-over redox potentials in the 821 emergence of metabolism (Nitschke and Russell 2011). Indeed, the gradient-rich mound- 822 scenario studies geological constraints for insights into the emergence of the universally 823 conserved proton-pump--an energy-producing vectorial process (Lane et al 2010; 824 Nitchske and Russell 2009), and where far-from-equilibrium conditions can produce 825 dynamic-cum-catalytic mineral structures (Mielke et al 2011; Sect.6.3). The higher 826 temperature inside the mound could have caused electrons (thermionic emission from 827 alloys) to flow in the direction of the redox gradient. It is interesting to consider the 828 electron passage through field-induced aggregates --expected to be substantial at the 829 gradient boundary-- wherein a reversibly bound particle would suffer a torque effect; this 830 homopolar-motor-like movement may have implications as precursors of rotary motors. 831 832 833 834 Table-II: Field-controlled colloids for a “scaffold-organization” a la Cairns-Smith 835 Field-control assisted Living system like Speculation based on ‘function’ characteristics theory/ reference/s 1a Field-controlled aggregates Confined, environment- Botet et al. 2001; (c.f. mineral layer sequences susceptible organization; Chantrell et al 1982; in crystal-organization distributed control on many Klokkenburg et al (Cairns-Smith 1982)). MNP- independent interacting 2006; Li et al 2007; network configuration units; global dynamics Pastor-Satorras and susceptible to external cannot dictate-- nor is Rubi 2000; Richardi influences: size of incoming predictable from--properties et al 2008; MNPs, fluxes, H-field, hosted of lower-level components, Rosenweig 1985; see reactions (could change local yet constrained by Klapp 2005, Sect.4, temperature or MNP’s redox feedback and references. state , thus its magnetic moment, etc.); these could impact transport (§4.6). 1b Coherent fields (H-field, Dissipating homogeneous Taketomi 2011; light, electric field) for sources to order Köhler and Hoffmann alignment, confinement of components into 2003; Riley et al MNPs into cooperative cooperative organization. 2002; Duan and Luo network; resemble 2 nd -order 2001 phase- transitions. 2 Close-to-equilibrium: Component-level: i) Weak, reversible dipolar i) Like weak exchange-coupling in interactions ~ k BT, sustain complementary binding particle-lattice; organization in space & time sustains organization in System-level: space & replicator in time dipolar-coupling ii) external fluctuations can ii) fluctuations harnessed by force be harnessed at component as components (work-cycles), well as at system level and evolving system 2a Diffusing-in MNPs aligning ‘template’-aided growth Speculation for open & expanding MNP-network (see (§4.3.1) system. Directed transport e.g. Ratchet-dynamics of Tierno et al 2008; nucleotide oligomer-bound molecular motors (see Tierno et al 2010 MNPs on garnet film) §4.3.1) 2b Magneto-structural transitions Component-level: as in De Lacheisserie et al (like 1 st –order) in particle work cycles of enzymes, 2005, see magnetic components motors. materials (§4.3.2) 2c Associative network ( c.f. System-level: susceptibility Hopfield 1982; Huke varying crystal sequences to ‘environment’/ and Lücke 2004; Cairns-Smith 1982 ) in evolution /analog memory Palm and Korenivski response to external changes 2009; 3 Potential for kinetic Flexible ‘templates’ help c.f. Baudry et al 2006 assistance in reactions plus juxtaposition of reactants trimmed phase-space of Like flow-reactor trimming see §1; c.f. Park and bound reactants limits phase space of bound Kim 2010 possible reactions (c.f. “side reactants, curtailing side activity” in crystal paradigm reactions. Cairns-Smith 2008) 4 Far-from-equilibrium: New self-organized Gryzbowski et al Dynamical structures via structures like swimmers, 2000, 2009; alternating H-fields/non- self-healing structures, and Osterman et al 2009; equilibrium conditions. others not seen in a static Snezhko 2011; Potential magnon-mode for field. Dreyfus et al 2005 energy propagation ( c.f. Field-tunable dispersions Patel and Mehta phonons in crystal lattice can trap/store optical (2011) (Cairns-Smith 2008) energy (like homogeneous ATP currency) 5 Transfer of heat through Long range energy transfer Phillip et al 2008; aligned aggregate. Shima et al 2009 6a Transfer of electrons (spin- Long range electron Pu et al 2007 polarized) through aggregate tunneling 6b Field-aligned aggregate for Chiral assemblies for Naaman and Zager spin-transmission (above) selective spin-transmission 2011 Magneto-optical properties: Analogous to properties of Davies and Llewelyn field-induced birefringence; biological matter 1980 Faraday rotation, ellipticity; linear, circular dichroism 6c Current carrying particle a la Vectorial proton-transfer due to Lorentz force homo-polar motor, §4.6 for torque in rotary motor 7 Effect of H/electric-fields on Resemblance to mitotic see Rosenberg et al MNP/thread suspensions spindle 1965 8 Merger of magnetic Horizontal -- assemblies from different pre- information/gene transfer biotic locales 836 837 838 839 840 841 842 843 5 Towards cooperative transitions: 844 845 In general, depletion forces (Asakura and Oosawa 1958; Marenduzzo et al 2006) 846 can enable aggregation in a given location provided there is an excess above a critical 847 concentration of interacting particles due to specific binding or anisotropic forces. Above 848 a threshold concentration, packing (translational) entropy stemming from shape 849 anisotropy (causing decrease in orientational at the cost of positional entropy) could help 850 overcome rotational entropy and break orientation symmetry, thus maximizing total 851 entropy (Onsager 1949 ; Dogic and Fraden 2005). This route could have been accessible to 852 rod-like mineral colloids (Davidson and Gabriel 2005; see Hamley 2003). Indeed, 853 mineral liquid crystals (Gabriel and Davidson 2003; Lemaire et al 2002; Vroege et al 854 2006; van den Pol et al 2010) appear promising as “readily available” candidates with 855 potential to provide a cooperative medium with sensitivity to environmental stimuli 856 (Cairns-Smith 2008), and this calls for a database of such minerals in prebiotic locales. 857 The route to LC phases has also been attempted directly from a mixture of organics using 858 entropic forces for achieving self-assembly. Nakata et al (2007) elegantly demonstrated 859 the assembly of short complementary double stranded DNA into LC aggregates . The 860 unpaired oligomers maximize their entropy via phase-separation of the rigid duplex- 861 forming oligomers into LC droplets (minimizing their volume). As mentioned earlier 862 (Sect.1, 3), to serve as effective conduits for energy flow the components of aggregates 863 en-route to life need to bind via weak cooperative interactions (c.f. weak/reversible and 864 transient yet specific complementary interactions enable execution of bio-functions). 865 Now we shall briefly review some experiments to explore the potential of field-controlled 866 aggregates to influence the phase-space of their organic guests, noting that alignment, 867 complementary binding interactions, and homo-chirality are important requirements 868 towards decreasing the excluded volume of packed molecules as in liquid crystalline 869 phases (Table-I). 870 5.1 Influencing the alignment/orientations of mineral-colloid-anchored organics 871 Field-aligned particles seem equipped for the scaffold requirement of influencing their 872 guest particles by transferring their externally-induced orienting ability to their anchored 873 organics. We imagine that in locations enriched in interacting organics (see below), 874 transitions in abiogenic polydisperse organics to LC-phases could have been aided via 875 coupling of their orientations with those of ‘doping’ low volume concentrations of 876 external field-aligned ferromagnetic particles ( a la “ferronematic” phases coined by 877 Brochard and de Gennes 1970), which could have increased the effective susceptibility of 878 the fledgling organic LCs. This decrease in the effective magnetic Frederiks threshold 879 could have led to their alignment and fractionation in the presence of weak H-fields. 880 Moreover, recent work (Podoliak et al 2011) suggests that although ferromagnetic 881 particles induce a low-field response, the intrinsic diamagnetic susceptibility of the 882 ferronematic comes to dominate its magnetic response behaviour-- a scenario intriguingly 883 reminiscent of Cairns-Smith’s ‘organic take-over’. 884 885 5.2 Increasing co-localization of interacting organic pairs 886 887 As abiogenic organics were unlikely to possess shape anisotropy, a high concentration of 888 complementary binding pairs with specific interactions would have been crucial for the 889 formation of LC phases. Indeed, for reasonable probabilities of collective transitions 890 from disordered to ordered mutually catalytic ensembles, the ingredients required are 891 simply stable and confined populations of molecules, whereby chance discrimination of 892 specific interactions could bring about catalysis; and increasing number of such mutual 893 interactions eventually causing catalytic reproduction of the whole set (Dyson 1999; 894 Kauffman 1993). Now, Hunding et al (2006) propose that a web of aggregates resulting 895 from selection and growth by complementary-binding between diverse pairs of molecules 896 across pre-biotic locales, can explain the emergence of specific interactions between like 897 and unlike molecules in life-processes. But abiogenics could have been present in diluted 898 solutions as well as high local concentrations via physical mechanisms (Budin and 899 Szostak 2010). To increase the concentration of complementary organic pairs in a given 900 location, consider a possible magnetic d.o.f. of the organic-bound mineral particles 901 (Sect.1). In contrast to specific binding interactions, non-specific binding in concentrated 902 media can be overcome by magnetic forces, thus offering a way to select pairs with 903 binding capacity above a threshold (see Ommering 2010). We suggest that, thanks to a 904 field’s ‘action at a distance’ capacity, its responsive particles—in the event of being 905 bound to one of a pair of complementary-binding organics – have the potential to 1) aid 906 the pairs to find each other by facilitating their detection in dilute to concentrated media 907 (e.g. Pan et al 2012); and 2) chaperone the recognition process to assist their binding (e.g. 908 Baudry et al 2006) thanks to flexibility of the colloidal field-aligned ‘templates’. Baudry 909 et al (2006) demonstrate how one-dimensional confinement of magnetic colloids in the 910 presence of an H-field considerably accelerates the recognition rate between grafted 911 receptors and their ligands, as measured by turbidometric detection of complexes in the 912 absence of the field. They suggest that since confinement significantly augments the 913 colliding frequency, the same also causes a large increase in the attempt frequency of 914 recognition. An extension of such experiments by first feeding the (open) system with a 915 slow input of nano-particles chemically conjugated to moieties like nucleotides/small 916 peptides-- and consequently checking for the incorporation of labeled complementary 917 units-- could be done in the absence/presence of an applied moderate H-field. Figures 4a 918 and 4b reproduce the experiments by Slater’s group (Ho et al 2009) who have used 919 magnetic templates to adhere magnetically labeled cells, to illustrate how a local field, 920 say from magnetic rocks (Sect.6) could have influenced the dynamics of magnetic 921 particle-anchored organics. 922 923 924 Figure 4a 925 926

927 928 Figure 4b 929 930 5.3 Homo-chirality 931 932 Perhaps the most intriguing implication of a role of magnetic-fields in life’s emergence 933 comes from the homo-chiral nature of its building blocks that respond differently to 934 left/right circularly-polarized light. Indeed, the findings (Carmeli et al; Naaman and 935 Zager 2011) have further fuelled this speculation by relating the capacity of scaled up 936 chiral assemblies of these building blocks to selectively transmit electrons according to 937 their spin-polarization. To explain in slightly more detail, Rosenfeld’s (Wagniere 2007) 938 chiral ‘rotational strength’ parameter m.d (a unique combination of P, T violating joint 939 PT conservation !) brings out the role of the magnetic part of the e.m. field in 940 ‘twisting/reorienting’ the magnetic moment about the field axis. Its interaction with the 941 electrical e.m.f. component causing electronic orbital transitions (by polarizing electron 942 cloud across the molecule) thus leads to transitions in a chiral molecule, with d and m 943 components being parallel and antiparallel, respectively, hence averaging out to zero for a 944 symmetric molecule. Feedback makes these interactions complex since oscillating H- 945 fields can cause charges to move and vice versa. A moving charge in turn affects the 946 properties of the carrier transporting it, and electrons have both charge and spin. Just as 947 an electron’s response to an electric or magnetic field shows up as a translation (via 948 charge) or rotation (via spin), likewise the response of its carrier to the electric and 949 magnetic fields is one of charge-translation or spin- rotation, respectively. In this context 950 recall the hypothesis of Garay et al (1973), viz. the electron magnetic moment and the 951 magnetic transition moment of the electronically excited chiral molecules could interact. 952 Thus, the magnetic transition dipole could influence the probability of the triplet state of 953 the optically active molecules, electron transport, and stereo-selectivity. Now, the 954 findings of Naaman’s group on orienting effects of weak H-fields on bio-membranes, 955 suggest that spin-transmission in the scaled-up versions of the chiral building blocks 956 follow analogous rules of magnetic interaction to those of the individual building blocks. 957 They reported unexpectedly high selectivity in transmission of spin-polarized electrons 958 that are consistent with giant magneto spin selectivity in inorganic magnetic films and 959 related colossal magneto-resistance effects. Here charge-transfer from metal substrate 960 converted adsorbed chiral bio-molecular layers from electric to magnetic dipoles, due to 961 cooperative effects. Charge redistribution leads to altered electronic structure via unpaired 962 electrons on adsorbed molecules, rendering them paramagnetic. Although spin-filtering 963 effects are achieved in spintronics by applying an external field to induce magnetization 964 in ferromagnetic thin films, magnetization in their bio-counterpart, i.e. a layered assembly 965 of dipolar chiral molecules, is based on two stages: 1) the H-field-created by transfer of 966 charge (electron/hole) through chiral molecules aligns the magnetic dipole of the charge 967 transferred; 2) then exchange interactions in the layered domain keeps them aligned. 968 969 These observations by Naaman’s group link up two seemingly unrelated aspects of 970 homo-chiral biological units, viz. selective spin-transmission by their scaled-up 971 assembled versions . In the background of the above discussion, it is gratifying to note 972 that this irreducible picture can be roughly met via H-field aligned colloids (Pu et al 973 2007; Sect.4.6 ) and thus could have helped a proto-metabolic reaction hosted on these 974 field-controlled aggregates. Now the picture of the transfer of high energy electrons to 975 sinks (like CO2) facilitating release of energy stresses on a pre-biotic location (Trefil et al 976 2009)-- and thus providing a thermodynamic incentive-- seems consistent with the picture 977 of functional ‘takeover’ by chiral organic assemblies a la Cairns-Smith wherein their 978 assembly from the building blocks would cause phase-space reduction. This is since 979 chiral asymmetric structures, such as helices, provide further scope of entropic 980 interaction-driven phase transitions: the excluded volume decreases in going from 981 packing parallel helices that are out-of-phase to in-phase ones, and at an angle to 982 facilitate interpenetration into each other’s chiral grooves (Barry et al 2006). As to the 983 source of engendered building blocks-- again in agreement with the two-level scaffold 984 paradigm -- note that field-controlled aggregates also have the potential to host the 985 formation of chiral organic guests. Although using a different source, Rosenberg (2011) 986 has demonstrated that substantial chiral-specific chemistry was induced by spin-polarized 987 electrons which were provided by radiating the magnetic substrate, adsorbing the chiral 988 organics, by an ionizing source. (The spin dependence of DOS near the Fermi energy in 989 magnetic matter suggests how the colloids could act as spin filters). This is apart from the 990 implications of field-controllable particles in asymmetric chemical synthesis (Ranganath 991 and Glorius 2011), and controlling chemical reactivity via spins (Buchachenko 2000). 992 993 6 Framboids and fractal forms; a magnetic-mechanism; the mound scenario; a fractal 994 scaffold organization: 995 996 6.1 Framboids and fractal framboids: As a possible scenario towards realizing a field- 997 controlled scaffold, we briefly look at framboids, whose raspberry-patterns inspire their 998 nomenclature. A number of structurally different minerals other than pyrite, i.e. copper 999 and zinc sulphides, greigite, magnetite, magnesioferrite, hematite, goethite, garnet, 1000 dolomite, opal, and even in phosphoric derivatives of allophone (Sawlowicz 2000)—form 1001 framboids, suggesting a physical mechanism of formation . Their formation is a dynamical 1002 self-organizing process: The nucleation of a supersaturated solution by the first-formed 1003 crystal triggers the separation of many crystals of the same size. Their ordering is an 1004 outcome of the interplay of close-packing attractive (such as surface-tension, magnetic) 1005 and repulsive (e.g. charge) forces (see Sawlowicz 2000). Next, studying their presence in 1006 sedimentary environments, Sawlowicz (1993) found framboids to be structured over a 1007 hierarchy of three size-scales: microframboids, to framboids, to polyframboids; he 1008 suggested the formation of nano-framboids, comprising microcluster aggregations (~ 1009 100atoms), by analogy with the 3-scale framboidal hierarchy. Pictures of polyframboids 1010 and aggregations of minute particles forming spherical grains (microframboids) in 1011 framboid are reproduced in Figure 5, from Sawlowicz (1993). Based on observations, 1012 Sawlowicz proposed a formation mechanism by which the original super-saturated gel- 1013 droplet would undergo subsequent divisions into immiscible smaller droplets; further 1014 subdivisions would depend on a number of factors (e.g. initial size, iron concentration, 1015 gel stabilization, viscosity, activity of sulphur species), wherein a key role is played by 1016 the colloid-gel phase in leading to the fractal forms. Also, the exclusion of organic 1017 compounds led to simple framboid formation via an aggregation mechanism, while in 1018 experiments with organic substance stabilized gel-droplets, fractal framboids formed by 1019 particulation. 1020 1021 1022 1023 1024 Figure 5 1025 1026 1027 6.2.1 Mineral ‘relics’: Besides having a striking resemblance to FeS clusters in ancient 1028 enzymes (Sect.6.3), the mineral greigite has magnetic properties. Now today’s enzymes 1029 control electron transfers in FeS clusters (Noodleman et al 1995; 2002) exploiting their 1030 sensitivity to local micro-environment fields (organic ligand, solvent, etc). This gels with 1031 the picture of controlling enzymes ‘taking over’ from functioning catalytic-cum-magnetic 1032 components of a field-controlled network. Further, from observations of (bio- 1033 mineralized) fractal greigite framboids (Preisinger and Aslanian 2004), it seems to be 1034 compatible with a nested organization; it can also be found in the magnetosomes of many 1035 bacteria (Reitner et al 2005; Simmons et al 2006). Indeed, magnetic mechanisms are 1036 hardly “unfamiliar” to living systems, being present across the kingdoms, and evolved at 1037 different times (Kirschvink and Hagadorn 2000; Posfai et al 2001; Winklhofer and 1038 Kirschvink 2010). 1039 1040 6.2.2 Magnetic mechanism: Wilkin and Barnes model 1041 1042 Wilkin and Barnes (1997) have explained the formation/stability of micro-meter sized 1043 pyrite framboids, using an interplay of negatively charged repulsive and magnetically 1044 attractive forces (in precursor greigite), where a size > 100nm would orient crystals to the 1045 weak geo-magnetic field ~ 70 microTesla. Assuming a spherical geometry, the critical 1046 grain diameter of constituent crystallites comprising the framboid interior d c = 2a, where 1/3 1047 a > 1, is given by d c = (6k BT/ µ 0πMsat |H|) . This result can be obtained from the 1048 inequality W WB > k BT where we define W WB ≡ µ0Msat V H. Here k B is Boltzmann’s 1049 constant and µ 0 the permeability of vacuum. When aligned parallel to the weak 1050 geomagnetic field (~ 70µT), d c = 0.1 µm. [Ferrimagnetic greigite has a saturation 1051 magnetization value M sat at 298K ranging between 110 and 130 kA/m. On the basis of 1052 microscopic observations by Hoffmann (1992) of natural greigite crystals, single-domain 1053 particles are roughly less than a micrometer in size]. 1054 1055 Now for an extension of this field-assembly mechanism to the nano-scale, an 1056 extrapolation using the above formula for d c shows that an H-field for accreting 10nm 1057 sized particles--as for ferrofluids-- would have to be ~1000-fold stronger than the weak 1058 geo-magnetic field. And as there was no trace of any geo-magnetic field at ~ 4.1-4.2 Ga 1059 (Hazen et al 2008), the time when Life is believed to have been already initiated (4.2-4.3 1060 Ga) (Russell and Hall 1997; 2006), we need extra-terrestrial sources, eg. meteoritic 1061 matter , for providing local H-fields (for e.g. see Sect.6.3 (next), Mitra-Delmotte and 1062 Mitra 2010a). 1063 1064 1065 6.3 The hydrothermal alkaline mound scenario and framboids 1066 1067 A colloid-gel environment in the Hadean with potential for magnetically formed 1068 framboids (Mielke et al 2011) is the alkaline seepage site mound scenario (Russell et al 1069 1994; see Sect.4.6), wherein greigite (Fe 3S4) provides the ‘continuity’ link to iron-sulphur 1070 clusters (Sect.6.2.1). Briefly (see Figure 6 reproduced from Russell and Martin (2004), 1071 and Russell and Hall (2006)), water percolating down through cracks in the hot ocean 1072 crusts would react exothermically with ferrous iron minerals, and return in convective - - - 1073 updrafts infused with H 2, NH 3, HCOO , HS , CH 3 ; this fluid (pH ~ 10 ≤ 120 C) would 2+ 1074 exhale into CO 2, Fe bearing ocean waters (pH ~ 5.5, ≤ 20 C), and create porous mounds 1075 consisting of brucite, Mg-rich clays, carbonates, Fe-Ni sulphide and green rust-- self- 1076 restoring reactors for titrating the hydrothermal fluid with the sea-water (Russell and 1077 Arndt 2005)-- towards reducing CO 2 (Russell et al 2005). Despite the low levels of 1078 bisulphide in alkaline solutions, (Mielke et al. 2010) have shown the potential of the 1079 hydrothermal solution to dissolve sulphydryl ions from sulphides in the crust that are 1080 expected to flow over ~30,000 years-- fulfilling the continuity of conditions required for 1081 abiogenesis. Here, the ensuing super-saturation in response to gradients (stark contrast of 1082 pH, temperature, etc.) would spontaneously result in colloidal precipitates of FeS 1083 (amongst other compounds, e.g. traces of W, Mo); these barriers would obstruct further 1084 mixing of the solutions, leading to the creation of non-equilibrium gradients (pH, redox, 1085 temperature; see Sect. 4.5-4.6) across these catalytic membranes, growing by 1086 hydrothermal inflation. And, abiogenic molecules (corresponding to metabolic/control 1087 levels) would coordinate with each other (Milner-White and Russell 2010; 2011) in 1088 inorganic compartments and dynamically ordered framboidal reaction sacs (Russell et al 1089 1989). 1090 1091 Indeed, spherical, ordered aggregates of framboidal pyrite (~ 5 µm diameter) were found 1092 in fossil hydrothermal chimneys (Boyce et al. 1983; Larter et al. 1981; see Figure 7 1093 provided by Boyce (PhD. Thesis, 1990). Further, Russell et al (1990) have noted the size 1094 similarities between magnetosome crystals and pyrite crystallites (~ 100nm in diameter) 1095 comprising the interior of framboids that seemed to have grown inorganically from the 1096 spherical shells of iron-sulphide gel. And, it is gratifying to see laboratory-formed 1097 membranes under non-equilibrium conditions revealing globular clusters that comprise or 1098 are attached to, the inner walls consisting of mackinawite and greigite (Mielke et al 1099 2011). These clusters (~1–10 micrometer diameter) resembling framboids, appeared 1100 similar to those in the fossilized chimneys, while the outermost crystalline layers were 1101 primarily composed of ferrous hydroxide [Fe(OH) 2] with an admixture of nanocrystalline 1102 mackinawite; the latter were located where the highly alkaline flow could have 1103 intercepted the ferrous iron-bearing fluid, and the former where the acidulous iron- 1104 bearing solutions could access the alkaline interior of the chimneys walls with 1105 concomitant precipitation of the framboids. 1106 1107 6.3.1 Extension of the mound scenario 1108 1109 Note that negatively-charged mineral greigite forming under mound conditions, where 1110 pH is well above 3 (Wilkins and Barnes 1997), resembles an aqueous-based ferrofluid. 1111 Significantly, the key to stabilizing its colloidal-gel state lies with organics (Rickard et al 1112 2001). The formation of colloidal magnetic minerals like greigite in the mound scenario 1113 makes it relevant to look for a control mechanism via an H-field, such as provided by 1114 rocks at the base of the mound. Primary magnetism is plausible via extraterrestrial 1115 meteoritic particles (unpublished work of Ostro and Russell; see Mitra-Delmotte and 1116 Mitra 2010a). And, this is expected to be reinforced by secondary magnetism thanks to 1117 serpentinization and production of magnetite. Magnetic networks can also bring together 1118 mechanisms harnessing different gradients via further colloidal/mineral precipitates 1119 enveloping the mound (c.f. H-field-influenced growth pattern of precipitated tubular 1120 structures, Stone and Goldstein 2004). 1121 1122 We saw (above) that the formation of precipitates leads to progressive growth of the 1123 chimneys: their growing front is soft and gel-like, whereas the chimney parts lower down 1124 harden as a result of aging. The progressive precipitation of colloidal particles containing 1125 magnetic components could have led to detrital remanent magnetism in the chimneys, 1126 thanks to the magnetic rock-field at the base of the mound, causing the physical 1127 alignment of the magnetic particles at the time of deposition. Thus chimneys/dendrites 1128 comprising magnetic minerals, and growing as a result of slower diffusion-aided 1129 processes, suggest that further magnetic ramifications such as spin-effects may have 1130 occurred within the thermal gels at the soft growing chimney front. Also, fractal 1131 aggregates—dendrites, framboids, etc.—show the possibility of reduction to lower size 1132 scales, and of being controlled by external fields (Botet et al 2001; c.f. electric-field, Tan 1133 et al 2000) . 1134 1135 1136 1137 1138 1139 1140 Figure 6 1141 1142 1143 1144 1145 1146 Figure 7 1147 1148 1149 6.4 Fractal-network of a guiding inorganic scaffold 1150 1151 The complexity of the environment-susceptible bio-system enables its adaptation; this 1152 computational task requires co-operative global dynamics of the autonomous units -- 1153 different gene-regulated processes. Indeed, Fernández and Solé (2004) invoke Boolean 1154 networks for capturing the global dynamics of complex bio-processes wherein higher- 1155 level behaviour results from interactions at the lower-level, and which cannot be 1156 predicted from the latter’s (unit/sub-process) details. Instead, they emphasize the need to 1157 focus on the nature (inhibiting/activating) of interactions between lower-level units, as 1158 well as the network-topology, viewing functional bio-networks as computing/task- 1159 performing devices. Moreover, efforts have been made to understand the robustness of 1160 biological networks in terms of their topology for possible design principles, assisting 1161 their evolution (Aldana and Cluzel 2003). Their frequent scale-free appearance has led to 1162 interest in networks with scale-free connectivity (many nodes with few connections and 1163 vice-versa) that are reportedly robust to random breakdowns; similarly also to the bigger 1164 class of small world networks – having a short path between any two nodes -- (Amaral et 1165 al. 2000) enabling fast communication between different nodes (Albert et al. 2000). 1166 Despite the appeal of these ideas, a clear consensus on a precise relationship between 1167 biology and network topology has yet to emerge (Khanin and Wit 2006); and the feature 1168 of robustness could signify why these or other similar networks came to be selected in 1169 evolution. Fractals (West and Goldberger 1987) have been noted for their capacity for 1170 “Fitting nearly infinite networks into finite spaces ” (Onaral and Cammarota 2000). 1171 Indeed, according to Ho (1997) a nested organization in biosystems permits processes to 1172 operate locally at equilibrium despite the whole system/subsystem maintaining itself far- 1173 from-equilibrium. Further, these dynamical patterns are realized via reversible gel-sol 1174 transitions, using the capacity of living systems to exist at the boundary of solid and 1175 liquid states (Trevors and Pollack 2005; Russell et al 1994). While universal fractal 1176 patterns in biology at the controlling level-I are likely to be the fruits of the processes of 1177 evolution and selection, such nested architecture could equally have been initially made 1178 available via inorganic scaffolds assisting guest-level-II processes. Since field-induced 1179 (dipolar) ordering offers an interaction mechanism that does not make use of any 1180 chemical or geometrical constraints of the particles, we speculate that this would enable 1181 the independently acting components to explore structural configurations at every scale. 1182 And, inspired by the observations of Russell et al (1989; 1990), Sawlowicz (1993; 2000), 1183 and Preisinger and Aslanian (2004), we have conjectured that moderate local magnetic 1184 fields could cause nested formations at the nano-scale as soft scaffolds for life’ 1185 emergence (see Merali 2007; Mitra and Mitra-Delmotte 2011; Mitra-Delmotte and Mitra 1186 2010a; 2010b; 2012). Further, in gradient-rich (redox, pH, temperature) environments, as 1187 in the mound, gradient-dissipating organic fractal structures (Seely and Macklem 2012)-- 1188 assembling from building blocks at level-II-- could have gradually replaced the 1189 functioning modules of the control-level-I inorganic networks. The tunability of inter- 1190 particle distances in the colloidal networks (above) via an H-field (and influencing 1191 percolation of heat and electrons (Sect.4.6)), also suggests a route for modulating the 1192 connectivity of organic networks (Kauffman 1993), the former providing an underlying 1193 manifold for guiding (c.f. Gershenson 2010) the organization of the latter. 1194 1195 7 Conclusions and scope 1196 1197 LC assemblies can be regarded as the minimal units of living systems sharing their 1198 environment-response behaviour that can be traced to cooperative interactions. Next, a 1199 simplified 2-tier projection of living systems shows the dependence of the metabolic 1200 network (level-II) on the control network of complex biomolecules with LC properties 1201 (level-I). Extrapolating this scenario to life’s origins, shows that macroscopic energy flow 1202 in the metabolic reaction cycles at level-II can be mapped to that in similar attractor 1203 cycles in pre-biotic locales. But no corresponding organic equivalents seem to be 1204 available for the control network (level-I), with microscopic energy transfers, and which 1205 lower kinetic barriers and catalyze level-II reactions. To that end, Cairns-Smith’s crystal- 1206 scaffold-- a level-I organization-- is extended to field-responsive mineral particles, since 1207 the intermediate regime between diffusion-limited and field-driven aggregation of 1208 anisotropic colloids seems capable of accessing the features of scaling and controlled 1209 mobility in disordered liquid medium. Such a cooperative manifold of reversible 1210 interactions achieved via coherent sources enables confinement (solid-phase-like), yet 1211 allows random sets of (MNP-bound) organics to interact (liquid-phase-like). Further, this 1212 LC-like cooperative organization is susceptible to external influences (size and magnetic 1213 moment of incoming MNPs, fluxes, etc) that can change its function-associated 1214 configuration, leading to feedback between guest and host levels. A function—of 1215 assisting a spontaneous process—associated with an organizational “whole” corresponds 1216 to the anatomy of bio-networks, and induces selection of the functional configuration. 1217 Again, via this susceptible configuration, the inorganic network can influence the 1218 evolution (irreversible) of its sterically-coupled organic guests (level-II) and cause their 1219 mutual coupling via an SOC-like mechanism. We speculate that the capacity to act as a 1220 low resistance channel of energy flow would have been a pre-requisite for a long range 1221 correlation scenario, towards becoming a computing system. Moreover its influence on 1222 the phase-space of its associated organics (Sect.5) would have oriented their assembly 1223 and dynamics towards a kinetic (Pross 2005) direction (breaking free from 1224 thermodynamic constraints). This would have poised the system for a series of phase- 1225 transitions with appropriate replacements “taking-over” the sustenance and continuity of 1226 its functions, till achievement of closure and life’s emergence. We hope the testable ideas 1227 presented here will motivate further research. 1228 1229 Acknowledgements 1230 1231 We are grateful to Prof. Michael Russell for inspiration and support (data, figures, key 1232 references). We thank him and Kirt Robinson for bringing the work of the Naaman’s 1233 group to our notice. For kind permission to reproduce their work we thank Dr. Adrian 1234 Boyce (labeled framboid pictures); Prof. Roy Chantrell (simulation of field-induced 1235 ordering in ferrofluids); Prof.Nigel Slater (magnetic cell patterning); and Prof. Z. 1236 Sawlowicz, (framboid pictures). We are grateful to the Reviewers for valuable 1237 suggestions and references, (e.g. Seely and Macklem 2012). GM-D is grateful to 1238 organizers and participants of the LIO Spring School for discussions, especially to 1239 Prof.Eors Szathmary for his criticism and suggestions on presentation. We thank Dr. 1240 B.M. Sodermark for suggestions (fractal structures); Prof. Anand K Bachhawat for 1241 encouragement; Gaetan Delmotte, Clarisse Grand for Hama-bead patterns (Figure 1); and 1242 Mr.Guy Delmotte for computer support. We are grateful to Dr. Jean-Jacques Delmotte for 1243 providing financial and infrastructural support. 1244 1245 1246 References 1247 1248 Adami, C. (1995). 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Phys. 93(6), 3457-3460. 2021 2022 2023 Yellen, B.B., Hovorka, O., and Friedman, G. (2005). Arranging matter by magnetic 2024 nanoparticle assemblers. Proc. Natl. Acad. Sci. U.S.A. 102(25), 8860–8864 2025 2026 Zheng, X., Zhou, S., Xiao, Y., Yu, X., Li, X., and Wu, P. (2009). Shape memory effect of 2027 poly(d,l-lactide)/Fe 3O4 nanocomposites by inductive heating of magnetite particles. 2028 Colloids Surf. B. Biointerfaces 71, 67–72. 2029 2030 2031 2032 2033 2034 Figure legends: 2035 2036 Figure 1: Towards facilitating the evolution of organic reactions/interactions (guest 2037 level-II) via a controlled inorganic scaffold (host- level-I) a la Cairns-Smith: a) The 2038 probability of forming complex stable dynamical patterns decreases with increasing 2039 number of organic molecules. This can be aided via selection by a pre-existing 2040 functioning organization—the crystal-scaffold or level-I (represented by a white pin 2041 board) acting as ‘traps’ for functioning assembled modules from level-II (represented by 2042 a ‘bottom-up assembly’ of coloured beads). For eg., a variety of recognition-like 2043 interactions between organic ‘building blocks’ are required (not all are shown) to 2044 construct the unit leading up to the four-fold symmetric structure. Shown on top is the 2045 new organic organization which has functionally replaced the original crystal one at 2046 level-I. b) To make this scenario compatible with soft colloidal dynamics and facilitate 2047 the ‘takeover’ of level-I by a hierarchy of functioning modules, we suggest a reversible 2048 field-stabilized scaffold with a modular organization—represented by a transparent pin 2049 board. A stable inorganic scaffold is also compatible with the simultaneous emergence of 2050 (and replacement by) different types of organic spatio-temporal correlations, and as each 2051 of these would be dependent on the scaffold, any external tinkering with the latter’s 2052 d.o.f.s, would also impact the different organic networks and facilitate their mutual 2053 coupling (see text). 2054 2055 Figure 2: Monte Carlos simulation in 2D: (a) clustering without H-field; (b) chaining 2056 under H-field (reproduced with kind permission from Chantrell et al 1982; see also 2057 Rosensweig 1985). 2058 2059 Figure 3: Speculated asymmetric interactive diffusion of further incoming ligand (L)- 2060 bound magnetic-nanoparticles (MNPs), represented in blue, through a field-induced MNP 2061 aggregate, represented in black (in aqueous medium) in response to a gentle gradient 2062 (non-homogeneous rock field). State 1/ State 2: lower/higher template-affinity states of 2063 the ligand (L) -bound MNP, in blue; green lines signify alignment in State 2; T.E. or 2064 thermal energy from bath; rock H-field direction indicated on top (Mitra-Delmotte and 2065 Mitra 2010a). A spatially non-homogeneous H-field is imagined (via magnetic rocks) that 2066 provides both detailed-balance breaking non-equilibrium and asymmetry, to a diffusing 2067 magnetic dipole undergoing infinitesimal spin-alignment changes. In addition to the 2068 external field and the bath fluctuations, its orientational state is influenced by the local H- 2069 fields of its “template” partners (forming the aggregate) that would periodically perturb 2070 its directed diffusion. This would lead to alternating low and high-‘template’-affinity 2071 states due to the dipole’s magnetic d.o.f., analogous to the isothermal release and binding 2072 cycles of the molecular machines on nucleic acid/protein templates, respectively. These 2073 changes would be similarly facilitated by thermal excitations from bath, with rectification 2074 by either the gentle H-field gradient or local template-partner H-fields (see text). 2075 2076 Figure 4 Patterning of magnetically labeled cells by Slater and coworkers (Ho et al 2077 2009): (a) Schematics of the procedure for magnetic cell labeling and patterning. A: 2078 Magnetic cell labeling. Cell membrane proteins were first biotinylated and subsequently 2079 labeled with streptavidin paramagnetic particles. B: Magnetic cell patterning. A star- 2080 shaped magnet was attached under the culture dish. Magnetically labeled cells were 2081 added and patterned onto the plate by the magnetic field. (b) Magnetic cell patterning of 2082 biotinylated human monocytes (HMs) labeled with streptavidin paramagnetic particles. 2083 A: Magnetically labeled HMs were successfully patterned by the star-shaped magnetic 2084 template. B: Magnetically labeled HMs were not patterned in the absence of the magnetic 2085 template. C: The non-labeled biotinylated HMs were patterned unsuccessfully by the 2086 magnetic template. D: Original magnetic template used to pattern HMs. E: Magnetic field 2087 profile of the magnetic star template used, as visualized by using iron filings to locate 2088 magnetic field maxima. Figures and legends taken from Ho et al (2009) with kind 2089 permission from Prof.Nigel Slater; "Copyright (2009) Royal Society of Medicine Press, 2090 UK". 2091 2092 2093 Figure 5: Development stages of pyrite framboids: scanning electron microscope image 2094 of (K) polyframboid; (L) aggregations of minute particles forming spherical grains 2095 (microframboids) in framboid; pictures reproduced from Sawlowicz (1993) with kind 2096 permission (single bar = 7 micrometer, double bar = 0.5 micrometer). 2097 2098 2099 Figure 6. The hydrothermal mound as an acetate and methane generator 2100 Steep physicochemical gradients are focused at the margin of the mound. The inset (cross 2101 section of the surface) illustrates the sites where anionic organic molecules are produced, 2102 constrained, react, and automatically organize to emerge as protolife (from Russell and 2103 Martin (2004), and Russell and Hall (2006), with kind permission). Compartmental pore 2104 space may have been partially filled with rapidly precipitated dendrites. The walls to the 2105 pores comprised nanocrystals of iron compounds, chiefly of FeS (Wolthers et al 2003) 2106 but including greigite, vivianite, and green rust occupying a silicate matrix. Tapping the 2107 ambient protonmotive force the pores and bubbles acted as catalytic culture chambers for − 2108 organic synthesis, open to H 2, NH 3, CH3 at their base, selectively permeable and semi- 2109 conducting at their upper surface. The font size of the chemical symbols gives a 2110 qualitative indication of the concentration of the reactants. 2111 2112 Figure 7 : Framboids in chimney : Small pyrite vent structure: Reflected ore microscopy 2113 of transverse section shows a central area of empty black spaces plus (grey) fine 2114 framboidal pyrite, and a fine euhedral authigenic rim surrounded by baryte, with minor 2115 pyrite; (Picture by Dr. Adrian Boyce reproduced with his kind permission; Source: Boyce 2116 et al. 1983; Boyce, A.J. (1990). Exhalation, sedimentation and sulphur isotope 2117 geochemistry of the Silvermines Zn + Pb + Ba deposits, County Tipperary, Ireland: 2118 Unpublished Ph.D. thesis , Glasgow, U.K., University of Strathclyde, 354 p.). 2119 2120 2121 2122 2123 2124 2125 2126 2127 Supplementary Information: Figures and Legends 2128 2129 2130

2131 2132 2133 Figure A 2134 2135 The feedback-coupling between the control-network (level-I) and the metabolic-network 2136 (level-II), is extrapolated to the pre-biotic era to rephrase Orgel’s (2000) concerns 2137 regarding plausible assumptions on the nature of minimal information- processing 2138 capabilities of mineral surfaces for hosting/organizing a proto-metabolic cycle. A 2139 capacity for interactions enabling long range energy and electron transfers (represented 2140 by bold orange and dashed blue arrows, respectively) is needed at level-I --the hosting 2141 surface, depicted as a green parallelogram,-- for proto-metabolic reaction cycles to 2142 organize at level-II—depicted as green hexagon. Did the host-surface at level-I have the 2143 ability to capture and channel the thermal energy released into it, say at point P (i.e. from 2144 an exothermic reaction taking place at level-II), to another spatio/temporal location, say 2145 point Q, where potential reactants (for endothermic reaction at level-II) could get 2146 recruited into the expanding cycle? Similarly electrons, required for some reactions of the 2147 cycle, would have led to exchanges (shown in blue dashed arrows) with the level-I 2148 catalytic colloids. 2149 2150 2151 2152 2153 2154 2155 2156 2157 2158 2159 2160 Figure B 2161 2162 The possibility of percolation through an inorganic network of dipolar interactions makes 2163 it interesting to consider a field-controlled network of magnetic mineral particles as a 2164 hosting surface to pre-biotic attractor cycles a la level-I. Figure B, is a top view of Figure 2165 A, where the green parallelogram representing the hosting surface is a “layer” of field- 2166 structured colloids, adapted from Figure 2, main text. 2167 We speculate that transfers of electrons and heat energy through the dipolar network 2168 (Sect. 4.6) could drive the magnetic system out of equilibrium. This is since each 2169 individual particle’s composite magnetic moment in turn is directly affected by its redox 2170 state, and also the local temperature, thus affecting their collective dynamics. Taken 2171 above a threshold these feedback effects have the potential to cause phase-transitions to 2172 regimes with new types of collective ordering, leading to a long range correlation. 2173 2174 2175 2176 2177 2178 2179 2180 2181 2182 2183 2184 2185 2186 2187 2188 2189 2190 2191 2192