Annual Review of Biophysics - Current Issue

Protein–protein association and aggregation are fundamental processes that play critical roles in various biological phenomena, from cellular signaling to disease progression. Understanding the underlying biophysical principles governing these processes is crucial for elucidating their mechanisms and developing strategies for therapeutic intervention. In this review, we provide an overview of recent experimental studies focused on protein–protein association and aggregation. We explore the key biophysical factors that influence these processes, including protein structure, conformational dynamics, and intermolecular interactions. We discuss the effects of environmental conditions such as temperature, pH and related buffer-specific effects, and ionic strength and related ion-specific effects on protein aggregation. The effects of polymer crowders and sugars are also addressed. We list the techniques used to study aggregation. We analyze emerging trends and challenges in the field, including the development of computational models and the integration of multidisciplinary approaches for a comprehensive understanding of protein–protein association and aggregation.

Structural biology is currently undergoing a transformation into dynamic structural biology, which reveals the dynamic structure of proteins during their functional activity to better elucidate how they function. Among the various approaches in dynamic structural biology, high-speed atomic force microscopy (HS-AFM) is unique in the ability to film individual molecules in dynamic action, although only topographical information is acquirable. This review provides a guide to the use of HS-AFM for biomolecular imaging and showcases several examples, as well as providing information on up-to-date progress in HS-AFM technology. Finally, we discuss the future prospects of HS-AFM in the context of dynamic structural biology in the upcoming era.

Over the past decades, our understanding of microbial metabolism has increased dramatically. Metabolomics, a family of techniques that are used to measure the quantities of small molecules in biological samples, has been central to these efforts. Advances in analytical chemistry have made it possible to measure the relative and absolute concentrations of more and more compounds with increasing levels of certainty. In this review, we highlight how metabolomics has contributed to understanding microbial metabolism and in what ways it can still be deployed to expand our systematic understanding of metabolism. To that end, we explain how metabolomics was used to (a) characterize network topologies of metabolism and its regulation networks, (b) elucidate the control of metabolic function, and (c) understand the molecular basis of higher-order phenomena. We also discuss areas of inquiry where technological advances should continue to increase the impact of metabolomics, as well as areas where our understanding is bottlenecked by other factors such as the availability of statistical and modeling frameworks that can extract biological meaning from metabolomics data.

The translation of messenger RNA (mRNA) into proteins represents the culmination of gene expression. Recent technological advances have revolutionized our ability to investigate this process with unprecedented precision, enabling the study of translation at the single-molecule level in real time within live cells. In this review, we provide an overview of single-mRNA translation reporters. We focus on the core technology, as well as the rapid development of complementary probes, tags, and accessories that enable the visualization and quantification of a wide array of translation dynamics. We then highlight notable studies that have utilized these reporters in model systems to address key biological questions. The high spatiotemporal resolution of these studies is shedding light on previously unseen phenomena, uncovering the full heterogeneity and complexity of translational regulation.

The rate of protein synthesis is slower than many folding reactions and varies depending on the synonymous codons encoding the protein sequence. Synonymous codon substitutions thus have the potential to regulate cotranslational protein folding mechanisms, and a growing number of proteins have been identified with folding mechanisms sensitive to codon usage. Typically, these proteins have complex folding pathways and kinetically stable native structures. Kinetically stable proteins may fold only once over their lifetime, and thus, codon-mediated regulation of the pioneer round of protein folding can have a lasting impact. Supporting an important role for codon usage in folding, conserved patterns of codon usage appear in homologous gene families, hinting at selection. Despite these exciting developments, there remains few experimental methods capable of quantifying translation elongation rates and cotranslational folding mechanisms in the cell, which challenges the development of a predictive understanding of how biology uses codons to regulate protein folding.

The relationship between genotype and phenotype, or the fitness landscape, is the foundation of genetic engineering and evolution. However, mapping fitness landscapes poses a major technical challenge due to the amount of quantifiable data that is required. Catalytic RNA is a special topic in the study of fitness landscapes due to its relatively small sequence space combined with its importance in synthetic biology. The combination of in vitro selection and high-throughput sequencing has recently provided empirical maps of both complete and local RNA fitness landscapes, but the astronomical size of sequence space limits purely experimental investigations. Next steps are likely to involve data-driven interpolation and extrapolation over sequence space using various machine learning techniques. We discuss recent progress in understanding RNA fitness landscapes, particularly with respect to protocells and machine representations of RNA. The confluence of technical advances may significantly impact synthetic biology in the near future.

A protein's sequence determines its conformational energy landscape. This, in turn, determines the protein's function. Understanding the evolution of new protein functions therefore requires understanding how mutations alter the protein energy landscape. Ancestral sequence reconstruction (ASR) has proven a valuable tool for tackling this problem. In ASR, one phylogenetically infers the sequences of ancient proteins, allowing characterization of their properties. When coupled to biophysical, biochemical, and functional characterization, ASR can reveal how historical mutations altered the energy landscape of ancient proteins, allowing the evolution of enzyme activity, altered conformations, binding specificity, oligomerization, and many other protein features. In this article, we review how ASR studies have been used to dissect the evolution of energy landscapes. We also discuss ASR studies that reveal how energy landscapes have shaped protein evolution. Finally, we propose that thinking about evolution from the perspective of an energy landscape can improve how we approach and interpret ASR studies.

Mitochondria are essential organelles performing important cellular functions ranging from bioenergetics and metabolism to apoptotic signaling and immune responses. They are highly dynamic at different structural and functional levels. Mitochondria have been shown to constantly undergo fusion and fission processes and dynamically interact with other organelles such as the endoplasmic reticulum, peroxisomes, and lipid droplets. The field of mitochondrial dynamics has evolved hand in hand with technological achievements including advanced fluorescence super-resolution nanoscopy. Dynamic remodeling of the cristae membrane within individual mitochondria, discovered very recently, opens up a further exciting layer of mitochondrial dynamics. In this review, we discuss mitochondrial dynamics at the following levels: (a) within an individual mitochondrion, (b) among mitochondria, and (c) between mitochondria and other organelles. Although the three tiers of mitochondrial dynamics have in the past been classified in a hierarchical manner, they are functionally connected and must act in a coordinated manner to maintain cellular functions and thus prevent various human diseases.

Myriad DNA-binding proteins undergo dynamic assembly, translocation, and conformational changes while on DNA or alter the physical configuration of the DNA substrate to control its metabolism. It is now possible to directly observe these activities—often central to the protein function—thanks to the advent of single-molecule fluorescence- and force-based techniques. In particular, the integration of fluorescence detection and force manipulation has unlocked multidimensional measurements of protein–DNA interactions and yielded unprecedented mechanistic insights into the biomolecular processes that orchestrate cellular life. In this review, we first introduce the different experimental geometries developed for single-molecule correlative force and fluorescence microscopy, with a focus on optical tweezers as the manipulation technique. We then describe the utility of these integrative platforms for imaging protein dynamics on DNA and chromatin, as well as their unique capabilities in generating complex DNA configurations and uncovering force-dependent protein behaviors. Finally, we give a perspective on the future directions of this emerging research field.

The interior of a living cell is an active, fluctuating, and crowded environment, yet it maintains a high level of coherent organization. This dichotomy is readily apparent in the intracellular transport system of the cell. Membrane-bound compartments called endosomes play a key role in carrying cargo, in conjunction with myriad components including cargo adaptor proteins, membrane sculptors, motor proteins, and the cytoskeleton. These components coordinate to effectively navigate the crowded cell interior and transport cargo to specific intracellular locations, even though the underlying protein interactions and enzymatic reactions exhibit stochastic behavior. A major challenge is to measure, analyze, and understand how, despite the inherent stochasticity of the constituent processes, the collective outcomes show an emergent spatiotemporal order that is precise and robust. This review focuses on this intriguing dichotomy, providing insights into the known mechanisms of noise suppression and noise utilization in intracellular transport processes, and also identifies opportunities for future inquiry.

Chromatin organization plays a critical role in cellular function by regulating access to genetic information. However, understanding chromatin folding is challenging due to its complex, multiscale nature. Significant progress has been made in studying in vitro systems, uncovering the structure of individual nucleosomes and their arrays, and elucidating the role of physicochemical forces in stabilizing these structures. Additionally, remarkable advancements have been achieved in characterizing chromatin organization in vivo, particularly at the whole-chromosome level, revealing important features such as chromatin loops, topologically associating domains, and nuclear compartments. However, bridging the gap between in vitro and in vivo studies remains challenging. The resemblance between in vitro and in vivo chromatin conformations and the relevance of internucleosomal interactions for chromatin folding in vivo are subjects of debate. This article reviews experimental and computational studies conducted at various length scales, highlighting the significance of intrinsic interactions between nucleosomes and their roles in chromatin folding in vivo.

Proteins often undergo large-scale conformational transitions, in which secondary and tertiary structure elements (loops, helices, and domains) change their structures or their positions with respect to each other. Simple considerations suggest that such dynamics should be relatively fast, but the functional cycles of many proteins are often relatively slow. Sophisticated experimental methods are starting to tackle this dichotomy and shed light on the contribution of large-scale conformational dynamics to protein function. In this review, we focus on the contribution of single-molecule Förster resonance energy transfer and nuclear magnetic resonance (NMR) spectroscopies to the study of conformational dynamics. We briefly describe the state of the art in each of these techniques and then point out their similarities and differences, as well as the relative strengths and weaknesses of each. Several case studies, in which the connection between fast conformational dynamics and slower function has been demonstrated, are then introduced and discussed. These examples include both enzymes and large protein machines, some of which have been studied by both NMR and fluorescence spectroscopies.

Genetically encoded fluorescent biosensors have revolutionized the study of cell signaling and metabolism, as they allow for live-cell measurements with high spatiotemporal resolution. This success has spurred the development of tailor-made biosensors that enable the study of dynamic phenomena on different timescales and length scales. In this review, we discuss different approaches to enhancing and developing new biosensors. We summarize the technologies used to gain structural insights into biosensor design and comment on useful screening technologies. Furthermore, we give an overview of different applications where biosensors have led to key advances over recent years. Finally, we give our perspective on where future work is bound to make a large impact.

The volumes of living cells undergo dynamic changes to maintain the cells’ structural and functional integrity in many physiological processes. Minor fluctuations in cell volume can serve as intrinsic signals that play a crucial role in cell fate determination during mechanotransduction. In this review, we discuss the variability of cell volume and its role in vivo, along with an overview of the mechanisms governing cell volume regulation. Additionally, we provide insights into the current approaches used to control cell volume in vitro. Furthermore, we summarize the biological implications of cell volume regulation and discuss recent advances in understanding the fundamental relationship between cell volume and mechanotransduction. Finally, we delve into the potential underlying mechanisms, including intracellular macromolecular crowding and cellular mechanics, that govern the global regulation of cell fate in response to changes in cell volume. By exploring the intricate interplay between cell volume and mechanotransduction, we underscore the importance of considering cell volume as a fundamental signaling cue to unravel the basic principles of mechanotransduction. Additionally, we propose future research directions that can extend our current understanding of cell volume in mechanotransduction. Overall, this review highlights the significance of considering cell volume as a fundamental signal in understanding the basic principles in mechanotransduction and points out the possibility of controlling cell volume to control cell fate, mitigate disease-related damage, and facilitate the healing of damaged tissues.

Biomolecular condensates are highly versatile membraneless organelles involved in a plethora of cellular processes. Recent years have witnessed growing evidence of the interaction of these droplets with membrane-bound cellular structures. Condensates’ adhesion to membranes can cause their mutual molding and regulation, and their interaction is of fundamental relevance to intracellular organization and communication, organelle remodeling, embryogenesis, and phagocytosis. In this article, we review advances in the understanding of membrane–condensate interactions, with a focus on in vitro models. These minimal systems allow the precise characterization and tuning of the material properties of both membranes and condensates and provide a workbench for visualizing the resulting morphologies and quantifying the interactions. These interactions can give rise to diverse biologically relevant phenomena, such as molecular-level restructuring of the membrane, nano- to microscale ruffling of the condensate–membrane interface, and coupling of the protein and lipid phases.

The structure and mechanism of the water-oxidation chemistry that occurs in photosystem II have been subjects of great interest. The advent of X-ray free electron lasers allowed the determination of structures of the stable intermediate states and of steps in the transitions between these intermediate states, bringing a new perspective to this field. The room-temperature structures collected as the photosynthetic water oxidation reaction proceeds in real time have provided important novel insights into the structural changes and the mechanism of the water oxidation reaction. The time-resolved measurements have also given us a view of how this reaction—which involves multielectron, multiproton processes—is facilitated by the interaction of the ligands and the protein residues in the oxygen-evolving complex. These structures have also provided a picture of the dynamics occurring in the channels within photosystem II that are involved in the transport of the substrate water to the catalytic center and protons to the bulk.

The mechanical phenotype of a cell determines its ability to deform under force and is therefore relevant to cellular functions that require changes in cell shape, such as migration or circulation through the microvasculature. On the practical level, the mechanical phenotype can be used as a global readout of the cell's functional state, a marker for disease diagnostics, or an input for tissue modeling. We focus our review on the current knowledge of structural components that contribute to the determination of the cellular mechanical properties and highlight the physiological processes in which the mechanical phenotype of the cells is of critical relevance. The ongoing efforts to understand how to efficiently measure and control the mechanical properties of cells will define the progress in the field and drive mechanical phenotyping toward clinical applications.

Dendritic spines are small, bulbous compartments that function as postsynaptic sites and undergo intense biochemical and biophysical activity. The role of the myriad signaling pathways that are implicated in synaptic plasticity is well studied. A recent abundance of quantitative experimental data has made the events associated with synaptic plasticity amenable to quantitative biophysical modeling. Spines are also fascinating biophysical computational units because spine geometry, signal transduction, and mechanics work in a complex feedback loop to tune synaptic plasticity. In this sense, ideas from modeling cell motility can inspire us to develop multiscale approaches for predictive modeling of synaptic plasticity. In this article, we review the key steps in postsynaptic plasticity with a specific focus on the impact of spine geometry on signaling, cytoskeleton rearrangement, and membrane mechanics. We summarize the main experimental observations and highlight how theory and computation can aid our understanding of these complex processes.

Integral membrane proteins (IMPs) play central roles in cellular physiology and represent the majority of known drug targets. Single-molecule fluorescence and fluorescence resonance energy transfer (FRET) methods have recently emerged as valuable tools for investigating structure–function relationships in IMPs. This review focuses on the practical foundations required for examining polytopic IMP function using single-molecule FRET (smFRET) and provides an overview of the technical and conceptual frameworks emerging from this area of investigation. In this context, we highlight the utility of smFRET methods to reveal transient conformational states critical to IMP function and the use of smFRET data to guide structural and drug mechanism-of-action investigations. We also identify frontiers where progress is likely to be paramount to advancing the field.

Cholesterol has been conjectured to be a modulator of the amyloid cascade, the mechanism that produces the amyloid-β (Aβ) peptides implicated in the onset of Alzheimer's disease. We propose that cholesterol impacts the genesis of Aβ not through direct interaction with proteins in the bilayer, but indirectly by inducing the liquid-ordered phase and accompanying liquid–liquid phase separations, which partition proteins in the amyloid cascade to different lipid domains and ultimately to different endocytotic pathways. We explore the full process of Aβ genesis in the context of liquid-ordered phases induced by cholesterol, including protein partitioning into lipid domains, mechanisms of endocytosis experienced by lipid domains and secretases, and pH-controlled activation of amyloid precursor protein secretases in specific endocytotic environments. Outstanding questions on the essential role of cholesterol in the amyloid cascade are identified for future studies.