Hydrogen atoms are produced when tryptophan within a protein is irradiated with ultraviolet light

Aromatic patterns: Tryptophan aromaticity as a catalyst for the emergence of life and rise of consciousness

Sunlight held the key to the origin of life on Earth. The earliest life forms, cyanobacteria, captured the sunlight to generate energy through photosynthesis. Life on Earth evolved in accordance with the circadian rhythms tied to sensitivity to sunlight patterns. A unique feature of cyanobacterial photosynthetic proteins and circadian rhythms' molecules, and later of nearly all photon-sensing molecules throughout evolution, is that the aromatic amino acid tryptophan (Trp) resides at the center of light-harvesting active sites. In this perspective, I review the literature and integrate evidence from different scientific fields to explore the role Trp plays in photon-sensing capabilities of living organisms through its resonance delocalization of π-electrons. The observations presented here are the product of apparently unrelated phenomena throughout evolution, but nevertheless share consistent patterns of photon-sensing by Trp-containing and Trp-derived molecules. I posit the unique capacity to transfer electrons during photosynthesis in the earliest life forms is conferred to Trp due to its aromaticity. I propose this ability evolved to assume more complex functions, serving as a host for mechanisms underlying mental aptitudes - a concept which provides a theoretical basis for defining the neural correlates of consciousness. The argument made here is that Trp aromaticity may have allowed for the inception of the mechanistic building blocks used to fabricate complexity in higher forms of life. More specifically, Trp aromatic non-locality may have acted as a catalyst for the emergence of consciousness by instigating long-range synchronization and stabilizing the large-scale coherence of neural networks, which mediate functional brain activity. The concepts proposed in this perspective provide a conceptual foundation that invites further interdisciplinary dialogue aimed at examining and defining the role of aromaticity (beyond Trp) in the emergence of life and consciousness.

Mass Spectrometry-Based Protein Footprinting for Higher-Order Structure Analysis: Fundamentals and Applications

Proteins adopt different higher-order structures (HOS) to enable their unique biological functions. Understanding the complexities of protein higher-order structures and dynamics requires integrated approaches, where mass spectrometry (MS) is now positioned to play a key role. One of those approaches is protein footprinting. Although the initial demonstration of footprinting was for the HOS determination of protein/nucleic acid binding, the concept was later adapted to MS-based protein HOS analysis, through which different covalent labeling approaches "mark" the solvent accessible surface area (SASA) of proteins to reflect protein HOS. Hydrogen-deuterium exchange (HDX), where deuterium in D2O replaces hydrogen of the backbone amides, is the most common example of footprinting. Its advantage is that the footprint reflects SASA and hydrogen bonding, whereas one drawback is the labeling is reversible. Another example of footprinting is slow irreversible labeling of functional groups on amino acid side chains by targeted reagents with high specificity, probing structural changes at selected sites. A third footprinting approach is by reactions with fast, irreversible labeling species that are highly reactive and footprint broadly several amino acid residue side chains on the time scale of submilliseconds. All of these covalent labeling approaches combine to constitute a problem-solving toolbox that enables mass spectrometry as a valuable tool for HOS elucidation. As there has been a growing need for MS-based protein footprinting in both academia and industry owing to its high throughput capability, prompt availability, and high spatial resolution, we present a summary of the history, descriptions, principles, mechanisms, and applications of these covalent labeling approaches. Moreover, their applications are highlighted according to the biological questions they can answer. This review is intended as a tutorial for MS-based protein HOS elucidation and as a reference for investigators seeking a MS-based tool to address structural questions in protein science.

An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning

Although empirical and neural studies show that serotonin (5HT) plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL)-framework. The model depicts the roles of dopamine (DA) and serotonin (5HT) in Basal Ganglia (BG). In this model, the DA signal is represented by the temporal difference error (δ), while the 5HT signal is represented by a parameter (α) that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: (1) Risk-sensitive decision making, where 5HT controls risk assessment, (2) Temporal reward prediction, where 5HT controls time-scale of reward prediction, and (3) Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG.