Lysosomes are the degradation centers and signaling hubs in the cell. Lysosomes undergo adaptation to maintain cell homeostasis in response to a wide variety of cues. Dysfunction of lysosomes leads to aging and severe diseases including lysosomal storage diseases (LSDs), neurodegenerative disorders, and cancer. To understand the complexity of lysosome biology, many research approaches and tools have been developed to investigate lysosomal functions and regulatory mechanisms in diverse experimental systems. This review summarizes the current approaches and tools adopted for studying lysosomes, and aims to provide a methodological overview of lysosomal research and related fields.

The lipid droplet (LD) is a conserved organelle that exists in almost all organisms, ranging from bacteria to mammals. Dysfunctions in LDs are linked to a range of human metabolic syndromes. The formation of protein complexes on LDs is crucial for maintaining their function. Investigating how proteins interact on LDs is essential for understanding the role of LDs. We have developed an effective method to uncover protein–protein interactions and protein complexes specifically on LDs. In this method, we conduct co-immunoprecipitation (co-IP) experiments using LD proteins extracted directly from isolated LDs, rather than utilizing proteins from cell lysates. To elaborate, we begin by purifying LDs with high-quality and extracting LD-associated proteins. Subsequently, the co-IP experiment is performed on these LD-associated proteins directly, which would enhance the co-IP experiment specificity of LD-associated proteins. This method enables researchers to directly unveil protein complexes on LDs and gain deeper insights into the functional roles of proteins associated with LDs.

Migrasomes are a novel type of cell organelle that form on the retraction fibers at the rear of migrating cells. In recent years, numerous studies have unveiled the mechanisms of migrasome formation and have highlighted significant roles of migrasomes in both physiological and pathological processes. Building upon the strategies outlined in published works and our own research experiences, we have compiled a comprehensive set of protocols for observing migrasomes. These step-by-step instructions encompass various aspects such as cell culture, labeling, imaging, in vitro reconstitution, and statistical analysis. We believe that these protocols serve as a valuable resource for researchers exploring migrasome biology.

Ribophagy, the cellular process wherein ribosomes are selectively self-digested through autophagy, plays a pivotal role in maintaining ribosome turnover. Understanding the molecular regulatory mechanisms governing ribophagy is pivotal to uncover its significance. Consequently, the establishment of methods for detecting ribophagy becomes important. In this protocol, we have optimized, enriched, and advanced existing ribophagy detection techniques, including immunoblotting, fluorescence microscopy, and transmission electron microscopy (TEM), to precisely monitor and quantify ribophagic events. Particularly noteworthy is the introduction of TEM technology for yeast ribophagy detection. In summary, the delineated methods are applicable for detecting ribophagy in both yeast and mammals, laying a solid foundation for further exploring the physiological importance of ribophagy and its potential implications in diverse cellular environments.

In animal cells, the Golgi apparatus serves as the central hub of the endomembrane secretory pathway. It is responsible for the processing, modification, and sorting of proteins and lipids. The unique stacking and ribbon-like architecture of the Golgi apparatus forms the foundation for its precise functionality. Under cellular stress or pathological conditions, the structure of the Golgi and its important glycosylation modification function may change. It is crucial to employ suitable methodologies to study the structure and function of the Golgi apparatus, particularly when assessing the involvement of a target protein in Golgi regulation. This article provides a comprehensive overview of the diverse microscopy techniques used to determine the specific location of the target protein within the Golgi apparatus. Additionally, it outlines methods for assessing changes in the Golgi structure and its glycosylation modification function following the knockout of the target gene.

The endoplasmic reticulum (ER) is an essential component of the endomembrane system in eukaryotes and plays a crucial role in protein and lipid synthesis, as well as the maintenance of calcium homeostasis. Morphologically, the ER is composed primarily of sheets and tubules. The tubular ER is composed of a network of tubular membrane structures, each with diameters ranging from 30 to 50 nanometers. In recent years, there has been in-depth research on the molecular mechanisms of membrane shaping and membrane fusion of the tubular ER. However, there is still limited understanding of the specific physiological functions of the tubular ER. Here, we report a protocol that combines differential centrifugation and immunoprecipitation to specifically enrich microsomes originating from the tubular ER in yeast. The ER tubule-derived microsomes can be further used for proteomic and lipidomic studies or other biochemical analyses.

Tumor metastasis, responsible for approximately 90% of cancer-associated mortality, remains poorly understood. Here in this study, we employed a melanoma lung metastasis model to screen for metastasis-related genes. By sequential tail vein injection of mouse melanoma B16F10 cells and the subsequently derived cells from lung metastasis into BALB/c mice, we successfully obtained highly metastatic B16F15 cells after five rounds of in vivo screening. RNA-sequencing analysis of B16F15 and B16F10 cells revealed a number of differentially expressed genes, some of these genes have previously been associated with tumor metastasis while others are novel discoveries. The identification of these metastasis-related genes not only improves our understanding of the metastasis mechanisms, but also provides potential diagnostic biomarkers and therapeutic targets for metastatic melanoma.

G protein-coupled receptors (GPCRs) are a large family of cell membrane proteins that are important targets for drug discovery. Nanobodies, also known as VHH (variable domains of heavy chain-only antibodies, HcAbs) antibodies, are small antibody fragments derived from camelids that have gained significant attention as potential therapeutics for targeting GPCRs due to their advantages over conventional antibodies. However, there are challenges in developing nanobodies targeting GPCRs, among which epitope accessibility is the most significant because the cell membrane partially shields the GPCR surface. We developed a universal protocol for making nanobodies targeting GPCRs using the cell membrane extract of GPCR-overexpressing HEK293 cells as the llama/alpaca immunization antigen. We constructed an immune VHH library and identified nanobodies by phage display bio-panning. The monoclonal nanobodies were recombinantly expressed in Escherichia coli (E. coli) and purified to characterize their binding potency.

Determining correlations between molecules at various levels is an important topic in molecular biology. Large language models have demonstrated a remarkable ability to capture correlations from large amounts of data in the field of natural language processing as well as image generation, and correlations captured from data using large language models can also be applicable to solving a wide range of specific tasks, hence large language models are also referred to as foundation models. The massive amount of data that exists in the field of molecular biology provides an excellent basis for the development of foundation models, and the recent emergence of foundation models in the field of molecular biology has really pushed the entire field forward. We summarize the foundation models developed based on RNA sequence data, DNA sequence data, protein sequence data, single-cell transcriptome data, and spatial transcriptome data respectively, and further discuss the research directions for the development of foundation models in molecular biology.

The prediction of affinity between TCRs and peptides is crucial for the further development of TIL (Tumor-Infiltrating Lymphocytes) immunotherapy. Inspired by the broader research of drug-protein interaction (DPI), we propose an atom-level peptide-TCR interaction (PTI) affinity prediction model APTAnet using natural language processing methods. APTAnet model achieved an average ROC-AUC and PR-AUC of 0.893 and 0.877, respectively, in ten-fold cross-validation on 25,675 pairs of PTI data. Furthermore, experimental results on an independent test set from the McPAS database showed that APTAnet outperformed the current mainstream models. Finally, through the validation on 11 cases of real tumor patient data, we found that the APTAnet model can effectively identify tumor peptides and screen tumor-specific TCRs.

ChatGPT explores a strategic blueprint of question answering (QA) to deliver medical diagnoses, treatment recommendations, and other healthcare support. This is achieved through the increasing incorporation of medical domain data via natural language processing (NLP) and multimodal paradigms. By transitioning the distribution of text, images, videos, and other modalities from the general domain to the medical domain, these techniques have accelerated the progress of medical domain question answering (MDQA). They bridge the gap between human natural language and sophisticated medical domain knowledge or expert-provided manual annotations, handling large-scale, diverse, unbalanced, or even unlabeled data analysis scenarios in medical contexts. Central to our focus is the utilization of language models and multimodal paradigms for medical question answering, aiming to guide the research community in selecting appropriate mechanisms for their specific medical research requirements. Specialized tasks such as unimodal-related question answering, reading comprehension, reasoning, diagnosis, relation extraction, probability modeling, and others, as well as multimodal-related tasks like vision question answering, image captioning, cross-modal retrieval, report summarization, and generation, are discussed in detail. Each section delves into the intricate specifics of the respective method under consideration. This paper highlights the structures and advancements of medical domain explorations against general domain methods, emphasizing their applications across different tasks and datasets. It also outlines current challenges and opportunities for future medical domain research, paving the way for continued innovation and application in this rapidly evolving field. This comprehensive review serves not only as an academic resource but also delineates the course for future probes and utilization in the field of medical question answering.

Optical tweezers have elucidated numerous biological processes, particularly by enabling the precise manipulation and measurement of tension. One question concerns the biological relevance of these experiments and the generalizability of these experiments to wider biological systems. Here, we categorize the applicability of the information garnered from optical tweezers in two distinct categories: the direct relevance of tension in biological systems, and what experiments under tension can tell us about biological systems, while these systems do not reach the same tension as the experiment, still, these artificial experimental systems reveal insights into the operations of biological machines and life processes.

Alzheimer’s disease (AD) has been conceptualized as a syndrome of brain network dysfunction. Recent imaging connectomics studies have provided unprecedented opportunities to map structural and functional brain networks in AD. By reviewing molecular, imaging, and computational modeling studies, we have shown that highly connected brain hubs are primarily distributed in the medial and lateral prefrontal, parietal, and temporal regions in healthy individuals and that the hubs are selectively and severely affected in AD as manifested by increased amyloid-beta deposition and regional atrophy, hypo-metabolism, and connectivity dysfunction. Furthermore, AD-related hub degeneration depends on the imaging modality with the most notable degeneration in the medial temporal hubs for morphological covariance networks, the prefrontal hubs for structural white matter networks, and in the medial parietal hubs for functional networks. Finally, the AD-related hub degeneration shows metabolic, molecular, and genetic correlates. Collectively, we conclude that the brain-network-hub-degeneration framework is promising to elucidate the biological mechanisms of network dysfunction in AD, which provides valuable information on potential diagnostic biomarkers and promising therapeutic targets for the disease.

Mitochondrial base editing tools hold great promise for the investigation and treatment of mitochondrial diseases. Mitochondrial DNA base editors (mitoBEs) integrate a programmable transcription-activator-like effector (TALE) protein with single-stranded DNA deaminase (TadA8e-V106W, APOBEC1, etc.) and nickase (MutH, Nt.BspD6I(C), etc.) to achieve heightened precision and efficiency in mitochondrial base editing. This innovative mitochondrial base editing tool exhibits a number of advantages, including strand-selectivity for editing, high efficiency, and the capacity to perform diverse types of base editing on the mitochondrial genome by employing various deaminases. In this context, we provide a detailed experimental protocol for mitoBEs to assist others in achieving proficient mitochondrial base editing.

Substrate stiffness is a microenvironment with a certain stiffness constructed by the extracellular matrix and adjacent cells, which plays an important role in the growth and development of cells and tissue formation. Studies have indicated that the stiffness of the brain is about 0.1–1 kPa. The physiological and pathological processes of the nervous system are mediated by the substrate stiffness that the neurons suffer. However, how substrate stiffness regulates these processes remains to be studied. Culturing neurons on substrates with different stiffness in vitro is one of the best methods to study the role of stiffness in regulating neuronal development and activity. In this study, by changing the preparation time and the activation time of polyacrylamide gel, we provide an improved method that achieves a low toxic substrate environment for better primary neuron adhesion and development. Hope that this method is convenient for those studying the role of substrate stiffness in neurons.

Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNAER) family proteins are the engines of most intra-cellular and exocytotic membrane fusion pathways (Jahn and Scheller 2006). Over the past two decades, in-vitro liposome fusion has been proven to be a powerful tool to reconstruct physiological SNARE-mediated membrane fusion processes (Liu et al. 2017). The reconstitution of the membrane fusion process not only provides direct evidence of the capability of the cognate SNARE complex in driving membrane fusion but also allows researchers to study the functional mechanisms of regulatory proteins in related pathways (Wickner and Rizo 2017). Heretofore, a variety of delicate methods for in-vitro SNARE-mediated liposome fusion have been established (Bao et al. 2018; Diao et al. 2012; Duzgunes 2003; Gong et al. 2015; Heo et al. 2021; Kiessling et al. 2015; Kreye et al. 2008; Kyoung et al. 2013; Liu et al. 2017; Scott et al. 2003). Although technological advances have made reconstitution more physiologically relevant, increasingly elaborate experimental procedures, instruments, and data processing algorithms nevertheless hinder the non-experts from setting up basic SNARE-mediated liposome fusion assays. Here, we describe a low-cost, timesaving, and easy-to-handle protocol to set up a foundational in-vitro SNARE-mediated liposome fusion assay based on our previous publications (Liu et al. 2023; Wang and Ma 2022). The protocol can be readily adapted to assess various types of SNARE-mediated membrane fusion and the actions of fusion regulators by using appropriate alternative additives (e.g., proteins, macromolecules, chemicals, etc.). The total time required for one round of the assay is typically two days and could be extremely compressed into one day.

Sedimentation solid-state NMR is a novel method for sample preparation in solid-state NMR (ssNMR) studies. It involves the sedimentation of soluble macromolecules such as large protein complexes. By utilizing ultra-high centrifugal forces, the molecules in solution are driven into a high-concentrated hydrogel, resulting in a sample suitable for solid-state NMR. This technique has the advantage of avoiding the need for chemical treatment, thus minimizing the loss of sample biological activity. Sediment ssNMR has been successfully applied to a variety of non-crystalline protein solids, significantly expanding the scope of solid-state NMR research. In theory, using this method, any biological macromolecule in solution can be transferred into a sedimented solute appropriate for solid-state NMR analysis. However, specialized equipment and careful handling are essential for effectively collecting and loading the sedimented solids to solid-state NMR rotors. To improve efficiency, we have designed a series of loading tools to achieve the loading process from the solution to the rotor in one step. In this paper, we illustrate the sample preparation process of sediment NMR using the H1.4-NCP¹⁶⁷ complex, which consists of linker histone H1.4 and nucleosome core particle, as an example.

The whole heart decellularized extracellular matrix (ECM) has become a promising scaffold material for cardiac tissue engineering. Our previous research has shown that the whole heart acellular matrix possesses the memory function regulating neural stem cells (NSCs) trans-differentiating to cardiac lineage cells. However, the cell subpopulations and phenotypes in the trans-differentiation of NSCs have not been clearly identified. Here, we performed single-cell RNA sequencing and identified 2,765 cells in the recellularized heart with NSCs revealing the cellular diversity of cardiac and neural lineage, confirming NSCs were capable of trans-differentiating into the cardiac lineage while maintaining the original ability to differentiate into the neural lineage. Notably, the trans-differentiated heart-like cells have dual signatures of neuroectoderm and cardiac mesoderm. This study unveils an in-depth mechanism underlying the trans-differentiation of NSCs and provides a new opportunity and theoretical basis for cardiac regeneration.

CX-5461, also known as pidnarulex, is a strong G4 stabilizer and has received FDA fast-track designation for BRCA1- and BRCA2- mutated cancers. However, quantitative measurements of the unfolding rates of CX-5461-G4 complexes which are important for the regulation function of G4s, remain lacking. Here, we employ single-molecule magnetic tweezers to measure the unfolding force distributions of c-MYC G4s in the presence of different concentrations of CX-5461. The unfolding force distributions exhibit three discrete levels of unfolding force peaks, corresponding to three binding modes. In combination with a fluorescent quenching assay and molecular docking to previously reported ligand-c-MYC G4 structure, we assigned the ~69 pN peak corresponding to the 1:1 (ligand:G4) complex where CX-5461 binds at the G4’s 5'-end. The ~84 pN peak is attributed to the 2:1 complex where CX-5461 occupies both the 5' and 3'. Furthermore, using the Bell-Arrhenius model to fit the unfolding force distributions, we determined the zero-force unfolding rates of 1:1, and 2:1 complexes to be (2.4 ± 0.9) × 10⁻⁸ s⁻¹ and (1.4 ± 1.0) × 10⁻⁹ s⁻¹ respectively. These findings provide valuable insights for the development of G4-targeted ligands to combat c-MYC-driven cancers.