Annual Review of Biophysics - Volume 49, 2020

The epithelial–mesenchymal transition (EMT) is a process by which cells lose epithelial traits, such as cell–cell adhesion and apico-basal polarity, and acquire migratory and invasive traits. EMT is crucial to embryonic development and wound healing. Misregulated EMT has been implicated in processes associated with cancer aggressiveness, including metastasis. Recent experimental advances such as single-cell analysis and temporal phenotypic characterization have established that EMT is a multistable process wherein cells exhibit and switch among multiple phenotypic states. This is in contrast to the classical perception of EMT as leading to a binary choice. Mathematical modeling has been at the forefront of this transformation for the field, not only providing a conceptual framework to integrate and analyze experimental data, but also making testable predictions. In this article, we review the key features and characteristics of EMT dynamics, with a focus on the mathematical modeling approaches that have been instrumental to obtaining various useful insights.

Many critical biological events, including biochemical signaling, membrane traffic, and cell motility, originate at membrane surfaces. Each such event requires that members of a specific group of proteins and lipids rapidly assemble together at a specific site on the membrane surface. Understanding the biophysical mechanisms that stabilize these assemblies is critical to decoding and controlling cellular functions. In this article, we review progress toward a quantitative biophysical understanding of the mechanisms that drive membrane heterogeneity and organization. We begin from a physical perspective, reviewing the fundamental principles and key experimental evidence behind each proposed mechanism. We then shift to a biological perspective, presenting key examples of the role of heterogeneity in biology and asking which physical mechanisms may be responsible. We close with an applied perspective, noting that membrane heterogeneity provides a novel therapeutic target that is being exploited by a growing number of studies at the interface of biology, physics, and engineering.

Mitochondria are essential organelles in eukaryotes. Most mitochondrial proteins are encoded by the nuclear genome and translated in the cytosol. Nuclear-encoded mitochondrial proteins need to be imported, processed, folded, and assembled into their functional states. To maintain protein homeostasis (proteostasis), mitochondria are equipped with a distinct set of quality control machineries. Deficiencies in such systems lead to mitochondrial dysfunction, which is a hallmark of aging and many human diseases, such as neurodegenerative diseases, cardiovascular diseases, and cancer. In this review, we discuss the unique challenges and solutions of proteostasis in mitochondria. The import machinery coordinates with mitochondrial proteases and chaperones to maintain the mitochondrial proteome. Moreover, mitochondrial proteostasis depends on cytosolic protein quality control mechanisms during crises. In turn, mitochondria facilitate cytosolic proteostasis. Increasing evidence suggests that enhancing mitochondrial proteostasis may hold therapeutic potential to protect against protein aggregation–associated cellular defects.

Recent advances in theory and algorithms for atomically detailed simulations open the way to the study of the kinetics of a wide range of molecular processes in biophysics. The theories propose a shift from the traditionally very long molecular dynamic trajectories, which are exact but may not be efficient in the study of kinetics, to the use of a large number of short trajectories. The short trajectories exploit a mapping to a mesh in coarse space and allow for efficient calculations of kinetics and thermodynamics. In this review, I focus on one theory: Milestoning is a theory and an algorithm that offers a hierarchical calculation of properties of interest, such as the free energy profile and the mean first passage time. Approximations to the true long-time dynamics can be computed efficiently and assessed at different steps of the investigation. The theory is discussed and illustrated using two biophysical examples: ion permeation through a phospholipid membrane and protein translocation through a channel.

Many enzymes appear to diffuse faster in the presence of substrate and to drift either up or down a concentration gradient of their substrate. Observations of these phenomena, termed enhanced enzyme diffusion (EED) and enzyme chemotaxis, respectively, lead to a novel view of enzymes as active matter. Enzyme chemotaxis and EED may be important in biology and could have practical applications in biotechnology and nanotechnology. They are also of considerable biophysical interest; indeed, their physical mechanisms are still quite uncertain. This review provides an analytic summary of experimental studies of these phenomena and of the mechanisms that have been proposed to explain them and offers a perspective on future directions for the field.

Many biomolecular condensates appear to form via spontaneous or driven processes that have the hallmarks of intracellular phase transitions. This suggests that a common underlying physical framework might govern the formation of functionally and compositionally unrelated biomolecular condensates. In this review, we summarize recent work that leverages a stickers-and-spacers framework adapted from the field of associative polymers for understanding how multivalent protein and RNA molecules drive phase transitions that give rise to biomolecular condensates. We discuss how the valence of stickers impacts the driving forces for condensate formation and elaborate on how stickers can be distinguished from spacers in different contexts. We touch on the impact of sticker- and spacer-mediated interactions on the rheological properties of condensates and show how the model can be mapped to known drivers of different types of biomolecular condensates.

The fundamental process of adaptive immunity relies on the differentiation of self from nonself. Nucleated cells are continuously monitored by effector cells of the immune system, which police the peptide status presented via cell surface molecules. Recent integrative structural approaches have provided insights toward our understanding of how sophisticated cellular machineries shape such hierarchical immune surveillance. Biophysical and structural achievements were invaluable for defining the interconnection of many key factors during antigen processing and presentation, and helped to solve several conundrums that persisted for many years. In this review, we illuminate the numerous quality control machineries involved in different steps during the maturation of major histocompatibility complex class I (MHC I) proteins, from their synthesis in the endoplasmic reticulum to folding and trafficking via the secretory pathway, optimization of antigenic cargo, final release to the cell surface, and engagement with their cognate receptors on cytotoxic T lymphocytes.

We review the adaptations of enzyme activity to different temperatures. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) from their mesophilic counterparts. Furthermore, there is increasing evidence that the temperature dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity versus temperature that is not accounted for by denaturation or unfolding. This is explained by macromolecular rate theory: A negative activation heat capacity for the rate-limiting chemical step leads directly to predictions of temperature optima; both entropy and enthalpy are temperature dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining experiment with molecular simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calculate relevant thermodynamic properties (such as activation enthalpies, entropies, and heat capacities) and reveal the molecular mechanisms underlying experimentally observed behavior.

The limits of evolution have long fascinated biologists. However, the causes of evolutionary constraint have remained elusive due to a poor mechanistic understanding of studied phenotypes. Recently, a range of innovative approaches have leveraged mechanistic information on regulatory networks and cellular biology. These methods combine systems biology models with population and single-cell quantification and with new genetic tools, and they have been applied to a range of complex cellular functions and engineered networks. In this article, we review these developments, which are revealing the mechanistic causes of epistasis at different levels of biological organization—in molecular recognition, within a single regulatory network, and between different networks—providing first indications of predictable features of evolutionary constraint.

Determining whether and how a gene is transcribed are two of the central processes of life. The conceptual basis for understanding such gene regulation arose from pioneering biophysical studies in eubacteria. However, eukaryotic genomes exhibit vastly greater complexity, which raises questions not addressed by this bacterial paradigm. First, how is information integrated from many widely separated binding sites to determine how a gene is transcribed? Second, does the presence of multiple energy-expending mechanisms, which are absent from eubacterial genomes, indicate that eukaryotes are capable of improved forms of genetic information processing? An updated biophysical foundation is needed to answer such questions. We describe the linear framework, a graph-based approach to Markov processes, and show that it can accommodate many previous studies in the field. Under the assumption of thermodynamic equilibrium, we introduce a language of higher-order cooperativities and show how it can rigorously quantify gene regulatory properties suggested by experiment. We point out that fundamental limits to information processing arise at thermodynamic equilibrium and can only be bypassed through energy expenditure. Finally, we outline some of the mathematical challenges that must be overcome to construct an improved biophysical understanding of gene regulation.

We discuss new developments in the nonequilibrium dynamics and thermodynamics of living systems, giving a few examples to demonstrate the importance of nonequilibrium thermodynamics for understanding biological dynamics and functions. We study single-molecule enzyme dynamics, in which the nonequilibrium thermodynamic and dynamic driving forces of chemical potential and flux are crucial for the emergence of non-Michaelis-Menten kinetics. We explore single-gene expression dynamics, in which nonequilibrium dissipation can suppress fluctuations. We investigate the cell cycle and identify the nutrition supply as the energy input that sustains the stability, speed, and coherence of cell cycle oscillation, from which the different vital phases of the cell cycle emerge. We examine neural decision-making processes and find the trade-offs among speed, accuracy, and thermodynamic costs that are important for neural function. Lastly, we consider the thermodynamic cost for specificity in cellular signaling and adaptation.

Liquid–liquid phase separation is emerging as the universal mechanism by which membraneless cellular granules form. Despite many previous studies on condensation of intrinsically disordered proteins and low complexity domains, we lack understanding about the role of RNA, which is the essential component of all ribonucleoprotein (RNP) granules. RNA, as an anionic polymer, is inherently an excellent platform for achieving multivalency and can accommodate many RNA binding proteins. Recent findings have highlighted the diverse function of RNA in tuning phase-separation propensity up or down, altering viscoelastic properties and thereby driving immiscibility between different condensates. In addition to contributing to the biophysical properties of droplets, RNA is a functionally critical constituent that defines the identity of cellular condensates and controls the temporal and spatial distribution of specific RNP granules. In this review, we summarize what we have learned so far about such roles of RNA in the context of in vitro and in vivo studies.

Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics.

Mitochondria are essential for eukaryotic life. These double-membrane organelles often form highly dynamic tubular networks interacting with many cellular structures. Their highly convoluted contiguous inner membrane compartmentalizes the organelle, which is crucial for mitochondrial function. Since the diameter of the mitochondrial tubules is generally close to the diffraction limit of light microscopy, it is often challenging, if not impossible, to visualize submitochondrial structures or protein distributions using conventional light microscopy. This renders super-resolution microscopy particularly valuable, and attractive, for studying mitochondria. Super-resolution microscopy encompasses a diverse set of approaches that extend resolution, as well as nanoscopy techniques that can even overcome the diffraction limit. In this review, we provide an overview of recent studies using super-resolution microscopy to investigate mitochondria, discuss the strengths and opportunities of the various methods in addressing specific questions in mitochondrial biology, and highlight potential future developments.

The FtsZ protein is a highly conserved bacterial tubulin homolog. In vivo, the functional form of FtsZ is the polymeric, ring-like structure (Z-ring) assembled at the future division site during cell division. While it is clear that the Z-ring plays an essential role in orchestrating cytokinesis, precisely what its functions are and how these functions are achieved remain elusive. In this article, we review what we have learned during the past decade about the Z-ring's structure, function, and dynamics, with a particular focus on insights generated by recent high-resolution imaging and single-molecule analyses. We suggest that the major function of the Z-ring is to govern nascent cell pole morphogenesis by directing the spatiotemporal distribution of septal cell wall remodeling enzymes through the Z-ring's GTP hydrolysis–dependent treadmilling dynamics. In this role, FtsZ functions in cell division as the counterpart of the cell shape–determining actin homolog MreB in cell elongation.