Communication theory and multicellular biology

Biophysical control of plasticity and patterning in regeneration and cancer

Cells and tissues display a remarkable range of plasticity and tissue-patterning activities that are emergent of complex signaling dynamics within their microenvironments. These properties, which when operating normally guide embryogenesis and regeneration, become highly disordered in diseases such as cancer. While morphogens and other molecular factors help determine the shapes of tissues and their patterned cellular organization, the parallel contributions of biophysical control mechanisms must be considered to accurately predict and model important processes such as growth, maturation, injury, repair, and senescence. We now know that mechanical, optical, electric, and electromagnetic signals are integral to cellular plasticity and tissue patterning. Because biophysical modalities underly interactions between cells and their extracellular matrices, including cell cycle, metabolism, migration, and differentiation, their applications as tuning dials for regenerative and anti-cancer therapies are being rapidly exploited. Despite this, the importance of cellular communication through biophysical signaling remains disproportionately underrepresented in the literature. Here, we provide a review of biophysical signaling modalities and known mechanisms that initiate, modulate, or inhibit plasticity and tissue patterning in models of regeneration and cancer. We also discuss current approaches in biomedical engineering that harness biophysical control mechanisms to model, characterize, diagnose, and treat disease states.

Conidia Fusion: A Mechanism for Fungal Adaptation to Nutrient-Poor Habitats

Conidia fusion (CF) is a commonly observed structure in fungi. However, it has not been systematically studied. This study examined 2457 strains of nematode-trapping fungi (NTF) to explore the species specificity, physiological period, and physiological significance of CF. The results demonstrated that only six species of Arthrobotrys can form CF among the sixty-five tested NTF species. The studies on the model species Arthrobotrys oligospora (DL228) showed that CF occurred in both shed and unshed plus mature and immature conidia. Additionally, the conidia fusion rate (CFR) increased significantly with the decrease of nutrient concentration in habitats. The studies on the conidia fusion body (CFB) produced by A. oligospora (DL228) revealed that the more conidia contained in the CFB, the faster and denser the mycelia of the CFB germinated in weak nutrient medium and soil plates. On the one hand, rapid mycelial extension is beneficial for the CFB to quickly find new nutrient sources in habitats with uneven nutrient distribution. On the other hand, dense mycelium increases the contact area with the environment, improving the nutrient absorption efficiency, which is conducive to improving the survival rate of conidia in the weak nutrient environment. In addition, all species that form CF produce smaller conidia. Based on this observation, CF may be a strategy to balance the defects (nutrient deficiency) caused by conidia miniaturization.

Expression of placental glycans and its role in regulating peripheral blood NK cells during preeclampsia: a perspective

Preeclampsia is a pregnancy-related multisystem disorder characterized by altered trophoblast invasion, oxidative stress, exacerbation of systemic inflammatory response, and endothelial damage. The pathogenesis includes hypertension and mild-to-severe microangiopathy in the kidney, liver, placenta, and brain. The main mechanisms involved in its pathogenesis have been proposed to limit trophoblast invasion and increase the release of extracellular vesicles from the syncytiotrophoblast into the maternal circulation, exacerbating the systemic inflammatory response. The placenta expresses glycans as part of its development and maternal immune tolerance during gestation. The expression profile of glycans at the maternal-fetal interface may play a fundamental role in physiological pregnancy changes and disorders such as preeclampsia. It is unclear whether glycans and their lectin-like receptors are involved in the mechanisms of maternal-fetal recognition by immune cells during pregnancy homeostasis. The expression profile of glycans appears to be altered in hypertensive disorders of pregnancy, which could lead to alterations in the placental microenvironment and vascular endothelium in pregnancy conditions such as preeclampsia. Glycans with immunomodulatory properties at the maternal-fetal interface are altered in early-onset severe preeclampsia, implying that innate immune system components, such as NK cells, exacerbate the systemic inflammatory response observed in preeclampsia. In this article, we discuss the evidence for the role of glycans in gestational physiology and the perspective of glycobiology on the pathophysiology of hypertensive disorders in gestation.

Quantifying information of intracellular signaling: progress with machine learning

Cells convey information about their extracellular environment to their core functional machineries. Studying the capacity of intracellular signaling pathways to transmit information addresses fundamental questions about living systems. Here, we review how information-theoretic approaches have been used to quantify information transmission by signaling pathways that are functionally pleiotropic and subject to molecular stochasticity. We describe how recent advances in machine learning have been leveraged to address the challenges of complex temporal trajectory datasets and how these have contributed to our understanding of how cells employ temporal coding to appropriately adapt to environmental perturbations.

Redox Electrochemistry to Interrogate and Control Biomolecular Communication

Cells often communicate by the secretion, transport, and perception of molecules. Information conveyed by molecules is encoded, transmitted, and decoded by cells within the context of the prevailing microenvironments. Conversely, in electronics, transmission reliability and message validation are predictable, robust, and less context dependent. In turn, many transformative advances have resulted by the formal consideration of information transfer. One way to explore this potential for biological systems is to create bio-device interfaces that facilitate bidirectional information transfer between biology and electronics. Redox reactions enable this linkage because reduction and oxidation mediate communication within biology and can be coupled with electronics. By manipulating redox reactions, one is able to combine the programmable features of electronics with the ability to interrogate and modulate biological function. In this review, we examine methods to electrochemically interrogate the various components of molecular communication using redox chemistry and to electronically control cell communication using redox electrogenetics.

Evolutionary origins of chemical synapses

Synaptic transmission is a fundamental neurobiological process by which neurons interact with each other and non-neuronal cells. It involves release of active substances from the presynaptic neuron onto receptive elements of postsynaptic cells, inducing waves of spreading electrochemical response. While much has been learned about the cellular and molecular mechanisms driving and governing transmitter release and sensing, the evolutionary origin of synaptic connections remains obscure. Herein, we review emerging evidence and concepts suggesting that key components of chemical synapse arose independently from neurons, in different functional and biological contexts, before the rise of multicellular living forms. We argue that throughout evolution, distinct synaptic constituents have been co-opted from ancestral forms for a new role in early metazoan, leading to the rise of chemical synapses and neurotransmission. Such a mosaic model of the origin of chemical synapses agrees with and supports the pluralistic hypothesis of evolutionary change.

Hierarchical patterning via dynamic sacrificial printing of stimuli-responsive hydrogels

Inspired by stimuli-tailored dynamic processes that spatiotemporally create structural and functional diversity in biology, a new hierarchical patterning strategy is proposed to induce the emergence of complex multidimensional structures via dynamic sacrificial printing of stimuli-responsive hydrogels. Using thermally responsive gelatin (Gel) and pH-responsive chitosan (Chit) as proof-of-concept materials, we demonstrate that the initially printed sacrificial material (Gel/Chit-H⁺ hydrogel with a single gelatin network) can be converted dynamically into non-sacrificial material (Gel/Chit-H⁺-Citr hydrogel with gelatin and an electrostatic citrate-chitosan dual network) under stimulus cues (citrate ions). Complex hierarchical structures and functions can be created by controlling either the printing patterns of citrate ink or the diffusion time of citrate ions into the Gel/Chit-H⁺ hydrogel. Specifically, mechanically anisotropic hydrogel film and cell patterning can be achieved via two-dimensional (2D) patterning; complex external and internal 3D structures can be fabricated in stimuli-responsive hydrogel and other hydrogels that are not stimuli-responsive under experimental conditions (also owing to the erasable properties of Gel/Chit-H⁺-Citr hydrogel) via 3D patterning; and an interconnected or segregated fluidic network can be constructed from the same initial 3D grid structure via 4D patterning. Our method is very simple, safe and generally reagentless, and the products/structures are often erasable, compatible and digestible, enabling advanced fabrication technologies (e.g. additive manufacturing) to be applied to a sustainable materials platform.

Spatial Nanomechanical Communications Based on State Transitions

In this paper, we present a novel framework of a nanomechanical communication (NMC) system where nanomechanical (NM) systems can communicate using mechanical movements to encode and transfer information between a transmitter (TX) nanomachine and a receiver (RX) nanomachine. First, some unique features of the envisioned NMC system have been presented in contrast to traditional communications systems. It is demonstrated that the encoding of distinct repeatable movements or motions is the key to information transfer in an NMC system. Using a state transition framework, we identify rest states (RSs) and motional degrees of freedom (MDoF) as the two essential concepts that determine the transmission rate of an NMC system in the spatial domain in two different modes, namely, synchronous and asynchronous transmissions. While the synchronous transmission is found to achieve much higher transmission rate compared to the asynchronous transmission in the noise-free case, the asynchronous mode is less restrictive and may have wider applicability. A stochastic model is considered to incorporate the influence of thermal noise in the system. A closed-form expression of the symbol error rate (SER) and its bounds have been derived for a particular symbol of a synchronous sliding motion NMC system with MDoF = 2. Numerical results show a promising SER performance in support of developing an NMC system model for nanoscale communications networks.

What is the resource footprint of a computer science department? Place, people, and Pedagogy

Internet and Communication Technology/electrical and electronic equipment (ICT/EEE) form the bedrock of today’s knowledge economy. This increasingly interconnected web of products, processes, services, and infrastructure is often invisible to the user, as are the resource costs behind them. This ecosystem of machine-to-machine and cyber-physical-system technologies has a myriad of (in)direct impacts on the lithosphere, biosphere, atmosphere, and hydrosphere. As key determinants of tomorrow’s digital world, academic institutions are critical sites for exploring ways to mitigate and/or eliminate negative impacts. This Report is a self-deliberation provoked by the questionHow do we create more resilient and healthier computer science departments: living laboratories for teaching and learning about resource-constrained computing, computation, and communication?Our response for University College London (UCL) Computer Science is to reflect on how, when, and where resources—energy, (raw) materials including water, space, and time—are consumed by the building (place), its occupants (people), and their activities (pedagogy). This perspective and attendant first-of-its-kind assessment outlines a roadmap and proposes high-level principles to aid our efforts, describing challenges and difficulties hindering quantification of the Department’s resource footprint. Qualitatively, we find a need to rematerialise the ICT/EEE ecosystem: to reveal the full costs of the seemingly intangible information society by interrogating the entire life history of paraphernalia from smartphones through servers to underground/undersea cables; another approach is demonstrating the corporeality of commonplace phrases and Nature-inspired terms such as artificial intelligence, social media, Big Data, smart cities/farming, the Internet, the Cloud, and the Web. We sketch routes to realising three interlinked aims: cap annual power consumption and greenhouse gas emissions, become a zero waste institution, and rejuvenate and (re)integrate the natural and built environments.

The Potential Role of Quorum Sensing in Clonal Growth and Subsequent Expansion of Bone Marrow Stromal Cell Strains in Culture

Clonal development (clonogenicity) is an inherent property of a subset of postnatal bone marrow (BM) adherent stromal mesenchymal stem cells (MSCs) from which a multipotent progeny develops in culture. Our data suggest that clonogenicity and BM-MSC expansion are two distinct biological events. This hypothesis is based on the following observations: (1) the beginning of clonal growth is a property strictly dependent on serum and independent of the social context, (2) the expansion of individual clone is influenced by events deriving from a social context during initial growth, (3) clonogenic cells grown in a social context in presence of serum can emancipate themselves to generate a secondary different progeny, and (4) the ability of socially generated clones to develop an inherent potential for further growth suggests that quorum sensing may operate in BM-MSC cultures and determine the potential growth of clonal strains.

On signalling and estimation limits for molecular birth-processes

Understanding and uncovering the mechanisms or motifs that molecular networks employ to regulate noise is a key problem in cell biology. As it is often difficult to obtain direct and detailed insight into these mechanisms, many studies instead focus on assessing the best precision attainable on the signalling pathways that compose these networks. Molecules signal one another over such pathways to solve noise regulating estimation and control problems. Quantifying the maximum precision of these solutions delimits what is achievable and allows hypotheses about underlying motifs to be tested without requiring detailed biological knowledge. The pathway capacity, which defines the maximum rate of transmitting information along it, is a widely used proxy for precision. Here it is shown, for estimation problems involving elementary yet biologically relevant birth-process networks, that capacity can be surprisingly misleading. A time-optimal signalling motif, called birth-following, is derived and proven to better the precision expected from the capacity, provided the maximum signalling rate constraint is large and the mean one above a certain threshold. When the maximum constraint is relaxed, perfect estimation is predicted by the capacity. However, the true achievable precision is found highly variable and sensitive to the mean constraint. Since the same capacity can map to different combinations of rate constraints, it can only equivocally measure precision. Deciphering the rate constraints on a signalling pathway may therefore be more important than computing its capacity.

Redox Is a Global Biodevice Information Processing Modality

Biology is well-known for its ability to communicate through (i) molecularly-specific signaling modalities and (ii) a globally-acting electrical modality associated with ion flow across biological membranes. Emerging research suggests that biology uses a third type of communication modality associated with a flow of electrons through reduction/oxidation (redox) reactions. This redox signaling modality appears to act globally and has features of both molecular and electrical modalities: since free electrons do not exist in aqueous solution, the electrons must flow through molecular intermediates that can be switched between two states - with electrons (reduced) or without electrons (oxidized). Importantly, this global redox modality is easily accessible through its electrical features using convenient electrochemical instrumentation. In this review, we explain this redox modality, describe our electrochemical measurements, and provide four examples demonstrating that redox enables communication between biology and electronics. The first two examples illustrate how redox probing can acquire biologically relevant information. The last two examples illustrate how redox inputs can transduce biologically-relevant transitions for patterning and the induction of a synbio transceiver for two-hop molecular communication. In summary, we believe redox provides a unique ability to bridge bio-device communication because simple electrochemical methods enable global access to biologically meaningful information. Further, we envision that redox may facilitate the application of information theory to the biological sciences.

Senomic view of the cell: Senome versus Genome

In the legacy of Thomas Henry Huxley, and his 'epigenetic' philosophy of biology, cells are proposed to represent a trinity of three memory-storing media: Senome, Epigenome, and Genome that together comprise a cell-wide informational architecture. Our current preferential focus on the Genome needs to be complemented by a similar focus on the Epigenome and a here proposed Senome, representing the sum of all the sensory experiences of the cognitive cell and its sensing apparatus. Only then will biology be in a position to embrace the whole complexity of the eukaryotic cell, understanding its true nature which allows the communicative assembly of cells in the form of sentient multicellular organisms.

Modeling the neuron as a nanocommunication system to identify spatiotemporal molecular events in neurodegenerative disease

AIM

In tauopathies such as Alzheimer's disease (AD), molecular changes spanning multiple subcellular compartments of the neuron contribute to neurodegeneration and altered axonal signaling. Computational modeling of end-to-end linked events benefit mechanistic analysis and can be informative to understand disease progression and accelerate development of effective therapies. In the calcium-amyloid beta model of AD, calcium ions that are an important regulator of neuronal function undergo dysregulated homeostasis that disrupts cargo loading for neurotrophic signaling along axonal microtubules (MTs). The aim of the present study was to develop a computational model of the neuron using a layered architecture simulation that enables us to evaluate the functionalities of several interlinked components in the calcium-amyloid beta model.

METHODS

The elevation of intracellular calcium levels is modeled upon binding of amyloid beta oligomers (AβOs) to calcium channels or as a result of membrane insertion of oligomeric Aβ1-42 to form pores/channels. The resulting subsequent Ca2+ disruption of dense core vesicle (DCV)-kinesin cargo loading and transport of brain-derived neurotrophic factor (BDNF) on axonal MTs are then evaluated. Our model applies published experimental data on calcium channel manipulation of DCV-BDNF and incorporates organizational complexity of the axon as bundled polar and discontinuous MTs. The interoperability simulation is based on the Institute of Electrical and Electronics Engineers standard association P1906.1 framework for nanoscale and molecular communication.

RESULTS

Our analysis provides new spatiotemporal insights into the end-to-end signaling events linking calcium dysregulation and BDNF transport and by simulation compares the relative impact of dysregulation of calcium levels by AβO-channel interactions, oligomeric Aβ1-42 pores/channel formation, and release of calcium by internal stores. The flexible platform of our model allows continued expansion of molecular details including mechanistic and morphological parameters of axonal cytoskeleton networks as they become available to test disease and treatment predictions.

CONCLUSION

The present model will benefit future drug studies on calcium homeostasis and dysregulation linked to measurable neural functional outcomes. The algorithms used can also link to other multiscale multi-cellular modeling platforms to fill in molecular gaps that we believe will assist in broadening and refining multiscale computational maps of neurodegeneration.

Touchable Computing: Computing-Inspired Bio-Detection

We propose a new computing-inspired bio-detection framework called touchable computing (TouchComp). Under the rubric of TouchComp, the best solution is the cancer to be detected, the parameter space is the tissue region at high risk of malignancy, and the agents are the nanorobots loaded with contrast medium molecules for tracking purpose. Subsequently, the cancer detection procedure (CDP) can be interpreted from the computational optimization perspective: a population of externally steerable agents (i.e., nanorobots) locate the optimal solution (i.e., cancer) by moving through the parameter space (i.e., tissue under screening), whose landscape (i.e., a prescribed feature of tissue environment) may be altered by these agents but the location of the best solution remains unchanged. One can then infer the landscape by observing the movement of agents by applying the "seeing-is-sensing" principle. The term "touchable" emphasizes the framework's similarity to controlling by touching the screen with a finger, where the external field for controlling and tracking acts as the finger. Given this analogy, we aim to answer the following profound question: can we look to the fertile field of computational optimization algorithms for solutions to achieve effective cancer detection that are fast, accurate, and robust? Along this line of thought, we consider the classical particle swarm optimization (PSO) as an example and propose the PSO-inspired CDP, which differs from the standard PSO by taking into account realistic in vivo propagation and controlling of nanorobots. Finally, we present comprehensive numerical examples to demonstrate the effectiveness of the PSO-inspired CDP for different blood flow velocity profiles caused by tumor-induced angiogenesis. The proposed TouchComp bio-detection framework may be regarded as one form of natural computing that employs natural materials to compute.

Information theory in systems biology. Part I: Gene regulatory and metabolic networks

"A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory.

Information theory in systems biology. Part II: protein-protein interaction and signaling networks

By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed.

The origins of multicellular organisms

Multicellularity has evolved in several eukaryotic lineages leading to plants, fungi, and animals. Theoretically, in each case, this involved (1) cell-to-cell adhesion with an alignment-of-fitness among cells, (2) cell-to-cell communication, cooperation, and specialization with an export-of-fitness to a multicellular organism, and (3) in some cases, a transition from "simple" to "complex" multicellularity. When mapped onto a matrix of morphologies based on developmental and physical rules for plants, these three phases help to identify a "unicellular ⇒ colonial ⇒ filamentous (unbranched ⇒ branched) ⇒ pseudoparenchymatous ⇒ parenchymatous" morphological transformation series that is consistent with trends observed within each of the three major plant clades. In contrast, a more direct "unicellular ⇒ colonial or siphonous ⇒ parenchymatous" series is observed in fungal and animal lineages. In these contexts, we discuss the roles played by the cooptation, expansion, and subsequent diversification of ancestral genomic toolkits and patterning modules during the evolution of multicellularity. We conclude that the extent to which multicellularity is achieved using the same toolkits and modules (and thus the extent to which multicellularity is homologous among different organisms) differs among clades and even among some closely related lineages.

Trachea-derived dpp controls adult midgut homeostasis in Drosophila

Homeostasis in adult tissues is maintained by resident stem cells and their progeny. Little is known about the regulation of tissue homeostasis by organ-organ interaction. Here we demonstrate that trachea-derived Decapentaplegic (Dpp), the main bone morphogenetic protein ligand in Drosophila, is essential for adult midgut homeostasis. We show that Dpp signaling is primarily activated in enterocytes (ECs). Depletion of Dpp signaling in ECs results in excess amounts of intestinal stem-cell-like cells and their progeny. Importantly, we find that Dpp is expressed specifically in tracheal cells that reach the intestinal cells through the visceral muscles. Depletion of dpp expression in tracheal cells phenocopies the Dpp loss-of-function defects in ECs. Our data demonstrate that the Drosophila trachea not only exchanges air for bodily needs but also produces a Dpp morphogen essential for neighboring tissue homeostasis. This work will provide important insights into the mechanisms of tissue homeostasis control by interorgan communication.

Systems biology. How information theory handles cell signaling and uncertainty

Information theory allows analyses of cell signaling capabilities without necessarily requiring detailed knowledge of the signaling networks.

The application of information theory to biochemical signaling systems

Cell signaling can be thought of fundamentally as an information transmission problem in which chemical messengers relay information about the external environment to the decision centers within a cell. Due to the biochemical nature of cellular signal transduction networks, molecular noise will inevitably limit the fidelity of any messages received and processed by a cell's signal transduction networks, leaving it with an imperfect impression of its environment. Fortunately, Shannon's information theory provides a mathematical framework independent of network complexity that can quantify the amount of information that can be transmitted despite biochemical noise. In particular, the channel capacity can be used to measure the maximum number of stimuli a cell can distinguish based upon the noisy responses of its signaling systems. Here, we provide a primer for quantitative biologists that covers fundamental concepts of information theory, highlights several key considerations when experimentally measuring channel capacity, and describes successful examples of the application of information theoretic analysis to biological signaling.

Biofabrication of stratified biofilm mimics for observation and control of bacterial signaling

Signaling between cells guides biological phenotype. Communications between individual cells, clusters of cells and populations exist in complex networks that, in sum, guide behavior. There are few experimental approaches that enable high content interrogation of individual and multicellular behaviors at length and time scales commensurate with the signal molecules and cells themselves. Here we present "biofabrication" in microfluidics as one approach that enables in-situ organization of living cells in microenvironments with spatiotemporal control and programmability. We construct bacterial biofilm mimics that offer detailed understanding and subsequent control of population-based quorum sensing (QS) behaviors in a manner decoupled from cell number. Our approach reveals signaling patterns among bacterial cells within a single biofilm as well as behaviors that are coordinated between two communicating biofilms. We envision versatile use of this biofabrication strategy for cell-cell interaction studies and small molecule drug discovery.

A novel coding method for gene mutation correction during protein translation process

In gene expression, gene mutations often lead to negative effect of protein translation in prokaryotic organisms. With consideration of the influences produced by gene mutation, a novel method based on error-correction coding theory is proposed for modeling and detection of translation initiation in this paper. In the proposed method, combined with a one-dimensional codebook from block coding, a decoding method based on the minimum hamming distance is designed for analysis of translation efficiency. The results show that the proposed method can recognize the biologically significant regions such as Shine-Dalgarno region within the mRNA leader sequences effectively. Also, a global analysis of single base and multiple bases mutations of the Shine-Dalgarno sequences are established. Compared with other published experimental methods for mutation analysis, the translation initiation can not be disturbed by multiple bases mutations using the proposed method, which shows the effectiveness of this method in improving the translation efficiency and its biological relevance for genetic regulatory system.

A framework for designing and analyzing binary decision-making strategies in cellular systems

Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway.

Extending Tlusty's rate distortion index theorem method to the glycome: do even 'low level' biochemical phenomena require sophisticated cognitive paradigms?

Unlike the universal genetic code and ordered protein folding, direct application of Tlusty's method to the glycome produces a reducto ad absurdum: From the beginning a complicated system of chemical cognition is needed so that external information constrains and tunes what would otherwise be a monstrously large 'glycan code error network'. Further, the glycan manufacture machinery itself must be regulated by yet other levels of chemical cognition to ensure that what is produced matches what was chosen for production. Application of a rate distortion index theorem/operator method at this second stage appears possible, permitting analytic characterization of the complicated 'glycan spectra' associated with cellular interactions and their dynamics. The regulation of 'low level' biochemical processes, ranging from gene expression and protein folding through the production of flexible glycan surface signalling fronds, appears to require systems of chemical cognition whose sophistication may rival that of high order neural process.