Easy and accurate protein structure prediction using ColabFold.

Since its public release in 2021, AlphaFold2 (AF2) has made investigating biological questions, by using predicted protein structures of single monomers or full complexes, a common practice. ColabFold-AF2 is an open-source Jupyter Notebook inside Google Colaboratory and a command-line tool that makes it easy to use AF2 while exposing its advanced options. ColabFold-AF2 shortens turnaround times of experiments because of its optimized usage of AF2's models. In this protocol, we guide the reader through ColabFold best practices by using three scenarios: (i) monomer prediction, (ii) complex prediction and (iii) conformation sampling. The first two scenarios cover classic static structure prediction and are demonstrated on the human glycosylphosphatidylinositol transamidase protein. The third scenario demonstrates an alternative use case of the AF2 models by predicting two conformations of the human alanine serine transporter 2. Users can run the protocol without computational expertise via Google Colaboratory or in a command-line environment for advanced users. Using Google Colaboratory, it takes <2 h to run each procedure. The data and code for this protocol are available at https://protocol.colabfold.com .

Spine muscle auto segmentation techniques in MRI imaging: a systematic review.

BACKGROUND: The accurate segmentation of spine muscles plays a crucial role in analyzing musculoskeletal disorders and designing effective rehabilitation strategies. Various imaging techniques such as MRI have been utilized to acquire muscle images, but the segmentation process remains complex and challenging due to the inherent complexity and variability of muscle structures. In this systematic review, we investigate and evaluate methods for automatic segmentation of spinal muscles. METHODS: Data for this study were obtained from PubMed/MEDLINE databases, employing a search methodology that includes the terms 'Segmentation spine muscle' within the title, abstract, and keywords to ensure a comprehensive and systematic compilation of relevant studies. Systematic reviews were not included in the study. RESULTS: Out of 369 related studies, we focused on 12 specific studies. All studies focused on segmentation of spine muscle use MRI, in this systematic review subjects such as healthy volunteers, back pain patients, ASD patient were included. MRI imaging was performed on devices from several manufacturers, including Siemens, GE. The study included automatic segmentation using AI, segmentation using PDFF, and segmentation using ROI. CONCLUSION: Despite advancements in spine muscle segmentation techniques, challenges still exist. The accuracy and precision of segmentation algorithms need to be improved to accurately delineate the different muscle structures in the spine. Robustness to variations in image quality, artifacts, and patient-specific characteristics is crucial for reliable segmentation results. Additionally, the availability of annotated datasets for training and validation purposes is essential for the development and evaluation of new segmentation algorithms. Future research should focus on addressing these challenges and developing more robust and accurate spine muscle segmentation techniques to enhance clinical assessment and treatment planning for musculoskeletal disorders.

A retrospective evaluation of individual thigh muscle volume disparities based on hip fracture types in followed-up patients: an AI-based segmentation approach using UNETR.

Background: Hip fractures are a common and debilitating condition, particularly among older adults. Loss of muscle mass and strength is a common consequence of hip fractures, which further contribute to functional decline and increased disability. Assessing changes in individual thigh muscles volume in follow-up patients can provide valuable insights into the quantitative recovery process and guide rehabilitation interventions. However, accurately measuring anatomical individual thigh muscle volume can be challenging due to various, labor intensive and time-consuming. Materials and Methods: This study aimed to evaluate differences in thigh muscle volume in followed-up hip fracture patients computed tomography (CT) scans using an AI based automatic muscle segmentation model. The study included a total of 18 patients at Gyeongsang National University, who had undergone surgical treatment for a hip fracture. We utilized the automatic segmentation algorithm which we have already developed using UNETR (U-net Transformer) architecture, performance dice score = 0.84, relative absolute volume difference 0.019 ± 0.017%. Results: The results revealed intertrochanteric fractures result in more significant muscle volume loss (females: -97.4 cm3, males: -178.2 cm3) compared to femoral neck fractures (females: -83 cm3, males: -147.2 cm3). Additionally, the study uncovered substantial disparities in the susceptibility to volume loss among specific thigh muscles, including the Vastus lateralis, Adductor longus and brevis, and Gluteus maximus, particularly in cases of intertrochanteric fractures. Conclusions: The use of an automatic muscle segmentation model based on deep learning algorithms enables efficient and accurate analysis of thigh muscle volume differences in followed up hip fracture patients. Our findings emphasize the significant muscle loss tied to sarcopenia, a critical condition among the elderly. Intertrochanteric fractures resulted in greater muscle volume deformities, especially in key muscle groups, across both genders. Notably, while most muscles exhibited volume reduction following hip fractures, the sartorius, vastus and gluteus groups demonstrated more significant disparities in individuals who sustained intertrochanteric fractures. This non-invasive approach provides valuable insights into the extent of muscle atrophy following hip fracture and can inform targeted rehabilitation interventions.

A compact six-axis force/torque sensor using photocouplers for impact robustness.

This paper presents a novel six-axis force/torque (F/T) sensor design for robotics, combining ease of manufacturing with compactness. It features a high measuring range of ∼3700 N, an exceptional resolution of 0.1 N, and a rapid 5 kHz sampling rate. The sensor's design, focusing on durability and a wider sensing range, utilizes noncontact sensors and a streamlined structure. A novel force sensing scheme aligns sensing elements in-plane on a single printed circuit board, reducing the part count to four and the weight to under 80 g, while integrating an analog-to-digital converter to eliminate the need for external communication devices. The lightweight, efficient prototype demonstrates a superior performance and a high response frequency, validated against a reference F/T sensor.

Precise individual muscle segmentation in whole thigh CT scans for sarcopenia assessment using U-net transformer.

The study aims to develop a deep learning based automatic segmentation approach using the UNETR(U-net Transformer) architecture to quantify the volume of individual thigh muscles(27 muscles in 5 groups) for Sarcopenia assessment. By automating the segmentation process, this approach improves the efficiency and accuracy of muscle volume calculation, facilitating a comprehensive understanding of muscle composition and its relationship to Sarcopenia. The study utilized a dataset of 72 whole thigh CT scans from hip fracture patients, annotated by two radiologists. The UNETR model was trained to perform precise voxel-level segmentation and various metrics such as dice score, average symmetric surface distance, volume correlation, relative absolute volume difference and Hausdorff distance were employed to evaluate the model's performance. Additionally, the correlation between Sarcopenia and individual thigh muscle volumes was examined. The proposed model demonstrated superior segmentation performance compared to the baseline model, achieving higher dice scores (DC = 0.84) and lower average symmetric surface distances (ASSD = 1.4191 ± 0.91). The volume correlation between Sarcopenia and individual thigh muscles in the male group. Furthermore, the correlation analysis of grouped thigh muscles also showed negative associations with Sarcopenia in the male participants. This thesis presents a deep learning based automatic segmentation approach for quantifying individual thigh muscle volume in sarcopenia assessment. The results highlights the associations between Sarcopenia and specific individual muscles as well as grouped thigh muscle regions, particularly in males. The proposed method improves the efficiency and accuracy of muscle volume calculation, contributing to a comprehensive evaluation of Sarcopenia. This research enhances our understanding of muscle composition and performance, providing valuable insights for effective interventions in Sarcopenia management.

Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data.

Background and Objectives: Hip fractures are commonly found in elderly patients, and often result in chronic pain and decreased physical function, as well as worsening of overall health. It is known that early surgical intervention during the acute phase and rehabilitation are important for improving clinical outcomes for these patients. However, the importance of management for improving the quality of life of these patients is becoming more emphasized. Studies on changes in sleep patterns after hip fractures are rare overseas. Therefore, the aim of this study is to investigate the prevalence of sleep disturbance in patients with hip fractures and to analyze the changes in sleep disturbance after surgery by comparing the preoperative and postoperative results. Materials and Methods: During the period from August 2022 to January 2023, patients who underwent surgical treatment for hip fractures and were recruited into the REAL Hip Cohort were selected as research subjects. The sleep survey was conducted using the Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 18 questions, each divided into areas of sleep quality, sleep latency, duration, efficiency, disturbance, use of medication, and daytime dysfunction. Each area is scored 0-3 points and the total is 0-21. A score greater than five indicates sleep disorder. The PSQI was surveyed during hospitalization and three months after surgery for post-fracture sleep status. To analyze changes before and after the fracture, paired T-tests and chi-square tests were performed. Results: From August 2022 to January 2023, a total of 40 patients who were recruited into the REAL Hip Cohort responded to the PSQI survey. The average age was 77.4 years and 36 were female. Sleep quality worsened from 0.75 ± 1.0 before surgery to 1.4 ± 1.0 three months after surgery (p = 0.019), and sleep efficiency also worsened from 0.4 ± 0.6 to 1.4 ± 1.0 (p < 0.001). The PSQI increased from an average of 5.2 ± 2.8 before surgery to 8.2 ± 4.2 three months after surgery (p = 0.007), and the number of patients who could be diagnosed with sleep disorders also increased from 12 (40%) to 24 (60%) (p = 0.030). Conclusions: A decline in overall sleep status was observed in patients in a survey on sleep patterns three months after hip fracture. Additional management is needed to improve their sleep patterns.

Boomerang latissimus dorsi flap in immediate or delayed breast reconstruction.

Background: Breast reconstruction using the latissimus dorsi (LD) flap is one of the most popular and common breast reconstruction techniques among Asian patients. There are increasing numbers of cases wherein breasts need to be reconstructed to moderate to large sizes among the Asian population. Most reconstructive surgeons use abdominal-based flaps-such as the deep inferior epigastric perforator and transverse rectus abdominis myocutaneous flap, or LD flap with an implant-to supplement the volume. Here, we compare the usefulness of the boomerang LD (bLD) flap-a technique developed by modifying the design of the conventional extended LD flap-with that of the LD flap with implant (LDi). Methods: This was a prospective cohort study including patients with breast cancer aged between 25 and 60 years who underwent unilateral total or skin/nipple-sparing mastectomy, or postmastectomy. The exclusion criteria were advanced breast cancer (stages 3 and 4); a history of cognitive impairment affecting ability to complete the self-reported questionnaire; a history of neurologic or musculoskeletal disorder; and a history of alcohol or drug abuse. Statistical analysis was performed, and correlations between the two technique types were analyzed [including age, body mass index, preoperative breast volume, operation time, flap elevation time, admission duration, adjuvant treatment (radiotherapy, chemotherapy), drain indwelling duration, and drain total sum volume]. Results: In total, 85 patients who underwent immediate breast construction through the LDi group (n=63) or bLD group (n=25) techniques after total mastectomy between January 2015 and June 2022 were analyzed (mean age: LDi group, 46±7.7 years; bLD group, 45.6±7.8 years). We observed that the flap weight, operative time, mean admission duration, and drain indwelling duration were statistically significantly different in the bLD group (P<0.05). Body mass index, preoperative breast volume, specimen weight, flap elevation time, and drain total time were comparable between groups. Conclusions: Breast reconstruction using the bLD flap was found to be a suitable alternative technique for patients who desire an autologous tissue transfer (rather than an implant) but are contraindicated for abdominal-based flaps and do not mind long postoperative scars.

A Comparison Study of Nipple-Areolar Complex Measurement: Light Detection and Ranging (LiDAR) Camera Versus Photometry.

BACKGROUND: In breast surgery, achieving esthetic outcomes with symmetry is crucial. The nipple-areolar complex (NAC) plays a significant role in breast characteristic measurement. Various technologies have advanced measurement techniques, and light detection and ranging (LiDAR) technology using three-dimensional scanning has been introduced in engineering. Increasing effort has been exerted to integrate such technologies into the medical field. This study focused on measuring NAC using a LiDAR camera, comparing it with traditional methods, and aimed to establish the clinical utility of LiDAR for obtaining favorable esthetic results. METHODS: A total of 44 patients, who underwent breast reconstruction surgery, and 65 NACs were enrolled. Measurements were taken (areolar width [AW], nipple width [NW] and nipple projection [NP]) using traditional methods (ruler and photometry) and LiDAR camera. To assess correlations and explore clinical implications, patient demographics and measurement values were collected. RESULTS: NAC measurements using a periscope and LiDAR methods were compared and correlated. LiDAR measurement accuracy was found to be high, with values above 95% for AW, NW and NP. Significant positive correlations were observed between measurements obtained through both methods for all parameters. When comparing body mass index, breast volume with AW and NW with NP, significant correlations were observed. These findings demonstrate the reliability and utility of LiDAR-based measurements in NAC profile assessment and provide valuable insights into the relationship between patient demographics and NAC parameters. CONCLUSIONS: LiDAR-based measurements are effective and can replace classical methods in NAC anthropometry, contributing to consistent and favorable esthetic outcomes in breast surgery. LEVEL OF EVIDENCE II: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors https://www.springer.com/00266 .

Robot-Assisted Latissimus Dorsi Flap Harvest for Partial Breast Reconstruction: Comparison With Endoscopic and Conventional Approaches.

BACKGROUND: Latissimus dorsi muscle flaps are widely utilized in breast reconstruction. Several methods have been introduced. OBJECTIVES: The aim was to compare the outcomes of robot-assisted breast reconstruction with a latissimus dorsi muscle flap following partial mastectomy with the outcomes of conventional and endoscopic-assisted techniques. METHODS: In this prospective single-institution study, Korean females diagnosed with breast cancer who underwent partial mastectomy and breast reconstruction with a latissimus dorsi flap from March 2020 to December 2021 were included. The outcomes of surgery and patient satisfaction utilizing the conventional, endoscopic-assisted, and robot-assisted techniques were compared. RESULTS: In total, 57 patients were included in this study, among whom 20 underwent conventional reconstruction, and 17 and 20 patients underwent endoscopic and robotic surgery, respectively. There was no statistically significant difference between the 3 methods in postoperative opioid analgesic dosage (P = .459), hospitalization period (P = .225), or the average total amount of donor site drainage during hospitalization (P = .175). With regard to patient satisfaction after surgery, especially regarding the donor site scar, the conventional method showed a significantly lower score than the other 2 techniques. CONCLUSIONS: Robot-assisted breast reconstruction with a latissimus dorsi muscle flap after partial mastectomy showed higher patient satisfaction than that for the conventional open method. Because robotic surgery is more convenient than the endoscopic technique, it is potentially a good alternative to conventional open or endoscopic surgery.

Subway station dust-induced pulmonary inflammation may be due to the dysfunction of alveolar macrophages: Possible contribution of bound elements.

With its increasing value as a means of public transportation, the health effects of the air in subway stations have attracted public concern. In the current study, we investigated the pulmonary toxicity of dust collected from an air purifier installed on the platform of the busiest subway station in Seoul. We found that the dust contained various elements which are attributable to the facilities and equipment used to operate the subway system. Particularly, iron (Fe), chromium (Cr), zirconium (Zr), barium (Ba), and molybdenum (Mo) levels were more notable in comparison with those in dust collected from the ventilation chamber of a subway station. To explore the health effects of inhaled dust, we first instilled via the trachea in ICR mice for 13 weeks. The total number of pulmonary macrophages increased significantly with the dose, accompanying hematological changes. Dust-laden alveolar macrophages and inflammatory cells accumulated in the perivascular regions in the lungs of the treated mice, and pulmonary levels of CXCL-1, TNF-α, and TGF-ß increased clearly compared with the control. The CCR5 and CD54 level expressed on BAL cell membranes was also enhanced following exposure to dust, whereas the CXCR2 level tended to decrease in the same samples. In addition, we treated the dust to alveolar macrophages (known as dust cells), lysosomal and mitochondrial function decreased, accompanied by cell death, and NO production was rapidly elevated with concentration. Moreover, the expression of autophagy- (p62) and anti-oxidant (SOD-2)-related proteins increased, and the expression of inflammation-related genes was dramatically up-regulated in the dust-treated cells. Therefore, we suggest that dysfunction of alveolar macrophages may importantly contribute to dust-induced inflammatory responses and that the exposure concentrations of Cr, Fe, Mo, Zr, and Ba should be considered carefully when assessing the health risks associated with subway dust. We also hypothesize that the bound elements may contribute to dust-induced macrophage dysfunction by inhibiting viability.

Foldcomp: a library and format for compressing and indexing large protein structure sets.

SUMMARY: Highly accurate protein structure predictors have generated hundreds of millions of protein structures; these pose a challenge in terms of storage and processing. Here, we present Foldcomp, a novel lossy structure compression algorithm, and indexing system to address this challenge. By using a combination of internal and Cartesian coordinates and a bi-directional NeRF-based strategy, Foldcomp improves the compression ratio by a factor of three compared to the next best method. Its reconstruction error of 0.08 Å is comparable to the best lossy compressor. It is five times faster than the next fastest compressor and competes with the fastest decompressors. With its multi-threading implementation and a Python interface that allows for easy database downloads and efficient querying of protein structures by accession, Foldcomp is a powerful tool for managing and analysing large collections of protein structures. AVAILABILITY AND IMPLEMENTATION: Foldcomp is a free open-source software (GPLv3) and available for Linux, macOS, and Windows at https://foldcomp.foldseek.com. Foldcomp provides the AlphaFold Swiss-Prot (2.9GB), TrEMBL (1.1TB), and ESMatlas HQ (114GB) database ready-for-download.

Genetically encoded fluorescent biosensors for GPCR research.

G protein-coupled receptors (GPCRs) regulate a wide range of physiological and pathophysiological cellular processes, thus it is important to understand how GPCRs are activated and function in various cellular contexts. In particular, the activation process of GPCRs is dynamically regulated upon various extracellular stimuli, and emerging evidence suggests the subcellular functions of GPCRs at endosomes and other organelles. Therefore, precise monitoring of the GPCR activation process with high spatiotemporal resolution is required to investigate the underlying molecular mechanisms of GPCR functions. In this review, we will introduce genetically encoded fluorescent biosensors that can precisely monitor the real-time GPCR activation process in live cells. The process includes the binding of extracellular GPCR ligands, conformational change of GPCR, recruitment of G proteins or ß-arrestin, GPCR internalization and trafficking, and the GPCR-related downstream signaling events. We will introduce fluorescent GPCR biosensors based on a variety of strategies such as fluorescent resonance energy transfer (FRET), bioluminescence resonance energy transfer (BRET), circular permuted fluorescent protein (cpFP), and nanobody. We will discuss the pros and cons of these GPCR biosensors as well as their applications in GPCR research.

Psychological and Biochemical Effects of an Online Pilates Intervention in Pregnant Women during COVID-19: A Randomized Pilot Study.

The purpose of this study was to analyze the effect of real-time online Pilates exercise during COVID-19 on women's body composition, blood lipids, and psychological health after childbirth. The participants were 16 pregnant women (24-28 weeks pregnant) enrolled at the C Women's Culture Center in Seoul, South Korea, classified into online Pilates groups and non-exercise groups (PE, n = 8; CON, n = 8). The online Pilates program was conducted for 8 weeks, twice a week, and 50 min a day using a real-time video chat app. Participants visited the hospital twice for body composition and blood tests. Questionnaires on postpartum depression, sleep disorder, and stress were conducted at 6 weeks and 12 weeks after childbirth. We found a significant difference between groups in body composition. The weight, percentage of body fat, body fat mass, and BMI of the PE group decreased. Blood lipids showed significant differences between the groups in TC, TG, LDL and CRP, while insulin and HDL showed no difference. All blood lipids, insulin, and CRP in the PE group were reduced. There were significant differences between the groups in postpartum depression, sleep disorders, and perceived stress indices performed in the post-test, and the serotonin concentration in the PE group increased. Serotonin levels were significantly correlated with postpartum depression, body fat mass, and body fat rate. Pregnant women's online Pilates in this study was effective at reducing weight and depression in women after childbirth and should be used to promote women's mental health during COVID-19.

Visualization of differential GPCR crosstalk in DRD1-DRD2 heterodimer upon different dopamine levels.

Dopaminergic signaling is regulated by transient micromolar (phasic) and background nanomolar (tonic) dopamine releases in the brain. These dopamine signals can be differentially translated by dopamine receptor type 1 and type 2, DRD1 and DRD2, which are G protein-coupled receptors (GPCRs). In response to dopamine, DRD1 and DRD2 are known to mediate opposite functions on cAMP production via Gs and Gi protein signaling. Interestingly, they can form a heterodimer. However, receptor crosstalk between DRD1-DRD2 heterodimers has not been directly measured, but it was only inferred from measuring downstream signaling pathways. Here we develop fluorescent protein-based multicolor biosensors which can monitor individual activation states of DRD1 and DRD2, and apply them to directly monitor the functional crosstalk between DRD1-DRD2 heterodimers in live cells. Utilizing these powerful tools, we surprisingly discover differential crosstalk in the DRD1-DRD2 heterodimers upon different dopamine (DA) levels: DRD1 activation is selectively inhibited at micromolar DA levels, while DRD2 is inhibited only by nanomolar DA concentration, implying a novel function of the DRD1-DRD2 heterodimer upon different DA levels. Our results imply differential receptor crosstalk and novel functions of the DRD1-DRD2 heterodimer in response to physiological dopamine levels from nanomolar to micromolar dopamine concentrations.

Developing a Scale Using Item Response Theory of the Self-Resilience in Taekwondo Players.

The purpose of this study was to identify the ego-resiliency of Taekwondo athletes and to develop a scale measuring such skills. We collected preliminary data using an open-ended online survey targeting Taekwondo athletes from nine countries (South Korea, China, Malaysia, United States, Spain, France, Brazil, United Kingdom, and Taiwan) who participated in international competitions between 2019 and 2020. We extracted participants' ego-resiliency from 48 survey responses, guided by expert meetings and a thorough literature review. We verified our Taekwondo ego-resiliency scale's construct validity using 741 survey responses. We utilized V coefficients, parallel analysis, an exploratory structural equation model, maximum likelihood, confirmatory factor analysis, and multi-group confirmatory factor analysis for data analysis. We identified four core ego-resiliency types: "empathy," "coach support," "care," and "parent support/effort". Our final measure, which demonstrated evidence of reliability and validity, comprises 18 items spanning 4 factors, with each item rated on a 3-point Likert scale.

ECG data dependency for atrial fibrillation detection based on residual networks.

Atrial fibrillation (AF) is an arrhythmia that can cause blood clot and may lead to stroke and heart failure. To detect AF, deep learning-based detection algorithms have recently been developed. However, deep learning models were often trained with limited datasets and were evaluated within the same datasets, which makes their performance generally drops on the external datasets, known as data dependency. For this study, three different databases from PhysioNet were used to investigate the data dependency of deep learning-based AF detection algorithm using the residual neural network (Resnet). Resnet 18, 34, 50 and 152 model were trained with raw electrocardiogram (ECG) signal extracted from independent database. The highest accuracy was about 98-99% which is evaluation results of test dataset from the own database. On the other hand, the lowest accuracy was about 53-92% which was evaluation results of the external dataset extracted from different source. There are data dependency according to the train dataset and the test dataset. However, the data dependency decreased as a large amount of train data.

Agrobacterium-Mediated Capsicum annuum Gene Editing in Two Cultivars, Hot Pepper CM334 and Bell Pepper Dempsey.

Peppers (Capsicum annuum L.) are the most widespread and cultivated species of Solanaceae in subtropical and temperate countries. These vegetables are economically attractive worldwide. Although whole-genome sequences of peppers and genome-editing tools are currently available, the precision editing of peppers is still in its infancy because of the lack of a stable pepper transformation method. Here, we employed three Agrobacterium tumefaciens strains-AGL1, EHA101, and GV3101-to investigate which Agrobacterium strain could be used for pepper transformation. Hot pepper CM334 and bell pepper Dempsey were chosen in this study. Agrobacterium tumefaciens GV3101 induced the highest number of calli in cv. Dempsey. All three strains generated similar numbers of calli for cv. CM334. We optimized a suitable concentration of phosphinothricin (PPT) to select a CRISPR/Cas9 binary vector (pBAtC) for both pepper types. Finally, we screened transformed calli for PPT resistance (1 and 5 mg/L PPT for cv. CM334 and Dempsey, respectively). These selected calli showed different indel frequencies from the non-transformed calli. However, the primary indel pattern was consistent with a 1-bp deletion at the target locus of the C. annuumMLO gene (CaMLO2). These results demonstrate the different sensitivity between cv. CM334 and Dempsey to A. tumefaciens-mediated callus induction, and a differential selection pressure of PPT via pBAtC binary vector.

Genetically Encoded Biosensors Based on Fluorescent Proteins.

Genetically encoded biosensors based on fluorescent proteins (FPs) allow for the real-time monitoring of molecular dynamics in space and time, which are crucial for the proper functioning and regulation of complex cellular processes. Depending on the types of molecular events to be monitored, different sensing strategies need to be applied for the best design of FP-based biosensors. Here, we review genetically encoded biosensors based on FPs with various sensing strategies, for example, translocation, fluorescence resonance energy transfer (FRET), reconstitution of split FP, pH sensitivity, maturation speed, and so on. We introduce general principles of each sensing strategy and discuss critical factors to be considered if available, then provide representative examples of these FP-based biosensors. These will help in designing the best sensing strategy for the successful development of new genetically encoded biosensors based on FPs.

Spatiotemporal Characterization of GPCR Activity and Function during Endosomal Trafficking Pathway.

G protein-coupled receptor (GPCR) is activated by extracellular signals. After their function at plasma membrane, GPCRs are internalized to be desensitized, while emerging evidence suggests that some GPCRs maintain their activity even after internalization. The endosomal trafficking pathway of a prototypic GPCR, ß adrenergic receptor 2 (B2AR), is in the range of several hours, however, spatiotemporal B2AR activity during this long-term endosomal trafficking pathway has not been characterized yet. Here, we analyze an agonist-induced real-time B2AR activity and its downstream function at the level of individual vesicles, utilizing a fluorescence resonance energy transfer (FRET)-based B2AR biosensor and cAMP reporters tethered at different trafficking stages of endosomes. Our results report that the internalized B2ARs sustain the activity and maintain the production of cAMP for several hours during the endosomal trafficking pathway. Temporal kinetics of B2AR activity is mathematically well explained by our active-vesicle population model modified from the Ricker model. Therefore, our GPCR monitoring system and a new kinetics model can be applied to understand the spatiotemporal GPCR activity and its downstream function during the endosomal trafficking pathway.

RhoA GTPase phosphorylated at tyrosine 42 by src kinase binds to ß-catenin and contributes transcriptional regulation of vimentin upon Wnt3A.

In the Wnt canonical pathway, Wnt3A has been known to stabilize ß-catenin. In the non-canonical Wnt signaling pathway, Wnt is known to activate Rho GTPases. The correlation between canonical and non-canonical pathways by Wnt signaling, however, has not been well elucidated. Here, we identified that Wnt3A promoted superoxide generation, leading to Tyr42 phosphorylation of RhoA through activations of c-Src and Rho-dependent coiled coil kinase 2 (ROCK2) and phosphorylation of p47phox, a component of NADPH oxidase. Wnt3A also induced accumulation of ß-catenin along with activations of RhoA and ROCK1. Concurrently, ROCK1 was able to phosphorylate GSK-3ß at Ser9, which phosphorylated Src at Ser51 and Ser492 residues, leading to Src inactivation through dephosphorylation of Tyr416 during the late period of Wnt3A treatment. Meanwhile, p-Tyr42 RhoA bound to ß-catenin via the N-terminal domain of ß-catenin, thereby leading to the nuclear translocation of p-Tyr42 RhoA/ß-catenin complex. Notably, p-Tyr42 RhoA as well as ß-catenin was associated with the promoter of Vim, leading to increased expression of vimentin. In addition, stomach cancer patients harboring higher expressed p-Tyr42 Rho levels revealed the much poorer survival probability. Therefore, we propose that p-Tyr42 RhoA is crucial for transcriptional regulation of specific target genes in the nucleus by binding to their promoters and involved in tumorigenesis.