Biology subjects

Fang, C.

Publications and source records attributed to Fang, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Glycaemic variability underlies myocyte dysfunction and myocardial injury risk in diabetes

Heart disease is the leading cause of morbidity and mortality in individuals with diabetes, due largely to risks associated with ischaemic injuries such as myocardial infarction (MI). We use human population genetic data to demonstrate that current biomarkers of hyperglycaemia do not account for risk of post-MI mortality in diabetes patients. This study therefore systematically evaluates glycaemic stress underpinning cardiovascular risk in diabetes. Using in vivo and in vitro models, we demonstrate that glycaemic variability rather than hyperglycaemia alone is a dominant risk factor for heart muscle dysfunction and myocardial injury sensitivity in diabetes. These findings provide new preclinical models for mechanistic and drug discovery studies and inform strategies for managing cardiovascular outcomes in patients with diabetes.

cell biology↗

bioRxiv2024

Cytosolic Carboxypeptidase 5 maintains mammalian ependymal multicilia to ensure proper homeostasis and functions of the brain

Ependymal multicilia position at one-side on the cell surface and beat synchronously across tissue to propel the flow of cerebrospinal fluid. Loss of ependymal cilia often causes hydrocephalus. However, molecules contributing to their maintenance remain yet fully revealed. Cytosolic carboxypeptidase (CCP) family are erasers of polyglutamylation, a conserved posttranslational modification of ciliary-axoneme microtubules. CCPs possess a unique domain (N-domain) N-terminal to their carboxypeptidase (CP) domain with unclear function. Here, we show that a novel mutant mouse of Agbl5, the gene encoding CCP5, with deletion of its N-terminus and partial CP domain (designated Agbl5M1/M1), developed lethal hydrocephalus due to degeneration of ependymal multicilia. Interestingly, multiciliogenesis was not impaired in Agbl5M1/M1 ependyma, but the initially formed multicilia beat in intercellularly diverse directions, indicative of aberrant tissue-level coordination. Moreover, actin networks are severely disrupted and basal body patches are improperly displaced in mutant cells, suggesting impaired cell level polarity. In contrast, Agbl5 mutants with disruption solely in the CP domain of CCP5 (Agbl5M2/M2) do not develop hydrocephalus despite increased glutamylation levels in ependymal cilia as similarly seen in Agbl5M1/M1. This study revealed an unappreciated role of CCP5, particularly its N-domain, in ependymal multicilia stability associated with their polarization and coordination.

cell biology↗

bioRxiv2024

Jan and mini-Jan, a model system for potato functional genomics

Potato (Solanum tuberosum) is the third most important food crop in the world. Although the potato genome has been fully sequenced, functional genomics research of potato lags relative to other major food crops due primarily to the lack of a model experimental potato line. Here, we present a diploid potato line, Jan, which possesses all essential characteristics for facile functional genomics studies. Jan has a high level of homozygosity after seven generations of self-pollination. Jan is vigorous and highly fertile with outstanding tuber traits, high regeneration rates, and excellent transformation efficiencies. We generated a chromosome-scale genome assembly for Jan, annotated genes, and identified syntelogs relative to the potato reference genome assembly DMv6.1 to facilitate functional genomics. To miniaturize plant architecture, we developed two "mini-Jan" lines with compact and dwarf plant stature using CRISPR/Cas9-mediated mutagenesis targeting the Dwarf and Erecta genes related to growth. Mini-Jan mutants are fully fertile and will permit higher-throughput studies in limited growth chamber and greenhouse space. Thus, Jan and mini-Jan provide an outstanding model system that can be leveraged for gene editing and functional genomics research in potato.

plant biology↗

bioRxiv2024

scCompass: An integrated cross-species scRNA-seq database for AI-ready

Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here we propose scCompass, which provides a data quality solution to build a large-scale, cross-species and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from 13 species and nearly 105 million single cells. Using this extensive dataset, we are able to archieve stable expression genes (SEGs) and organ-specific expression genes (OSGs) in human and mouse. We provide different scalable datasets that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art (SOTA) single-cell foundataion models. In summary, the AI-readiness of scCompass, which combined with user-friendly data sharing, visualization and online analysis, greatly simplifies data access and exploitation for researchers in single cell biology(http://www.bdbe.cn/kun).

bioinformatics↗

bioRxiv2024

Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding

Forming an episodic memory requires binding together disparate elements that co-occur in a single experience. One model of this process is that neurons representing different components of a memory bind to an "index" -- a subset of neurons unique to that memory. Evidence for this model has recently been found in chickadees, which use hippocampal memory to store and recall locations of cached food. Chickadee hippocampus produces sparse, high-dimensional patterns ("barcodes") that uniquely specify each caching event. Unexpectedly, the same neurons that participate in barcodes also exhibit conventional place tuning. It is unknown how barcode activity is generated, and what role it plays in memory formation and retrieval. It is also unclear how a memory index (e.g. barcodes) could function in the same neural population that represents memory content (e.g. place). Here, we design a biologically plausible model that generates barcodes and uses them to bind experiential content. Our model generates barcodes from place inputs through the chaotic dynamics of a recurrent neural network and uses Hebbian plasticity to store barcodes as attractor states. The model matches experimental observations that memory indices (barcodes) and content signals (place tuning) are randomly intermixed in the activity of single neurons. We demonstrate that barcodes reduce memory interference between correlated experiences. We also show that place tuning plays a complementary role to barcodes, enabling flexible, contextually-appropriate memory retrieval. Finally, our model is compatible with previous models of the hippocampus as generating a predictive map. Distinct predictive and indexing functions of the network are achieved via an adjustment of global recurrent gain. Our results suggest how the hippocampus may use barcodes to resolve fundamental tensions between memory specificity (pattern separation) and flexible recall (pattern completion) in general memory systems.

neuroscience↗

bioRxiv2024

A community-oriented, data-driven resource to improve protocol design for cardiac modelling from human pluripotent stem cells

Protocol design and benchmarking is central to optimising model development using human pluripotent stem cell derived cardiomyocytes (hPSC-CMs). By applying data mining to decades of research and hundreds of peer reviewed studies, we evaluate how protocol variables associate with common properties of cardiac functional and physiological maturation. This resource is publicly accessible through CMPortal, a community-oriented website that provides data-driven tools for researchers to navigate leverage decades of knowledge for benchmarking protocol designs and outcomes for their dedicated applications in developmental biology, disease modelling, and drug screening.

developmental biology↗

bioRxiv2024

GageTracker: a tool for dating gene age by micro- and macro-synteny with high speed and accuracy

With the advent of the Earth Genome Project, an increasing number of species' genomes presents exciting opportunities for exploring genetic and phenotypic diversity in organisms. Determining the origin time of genes facilitates the elucidation of crucial genetic mechanisms underlying significant biological evolutionary questions such as the transition from aquatic to terrestrial life, the emergence of mammals, the origin of humans, as well as the development of species- or lineage-specific traits. However, accurately determining the origin time of these genes in species separated by long evolutionary distances remains a major challenge in bioinformatics as these genes often undergo significant changes in their genome sequences, making it difficult to trace them back to their origin. Here, we proposed a new approach for dating gene age based on the micro- and macro-synteny algorithms. This approach employs the parallel computation of orthologous genome alignments across multiple species. Our method was integrated into the GageTracker (Gene Age Tracker) software, providing a fast and accurate way to trace gene age with minimal user input, available at https://github.com/RiversDong/GageTracker. Benchmarked against the simMammals dataset (Alignathon), GageTracker achieved the same high-quality genome alignments as the optimized LastZ aligner, but improved operation speed by 1.4-7 times. In a separate analysis of 12 Drosophila genomes, GageTracker efficiently assessed the ages of 23,720 genes (including ~13,965 protein-coding genes) in just ~22 hours with default parameters. When comparing with the GenTree database (recognized as the most comprehensive and accurate tool for evaluating gene age), GageTracker achieved an impressive ~94.4% accuracy and ~99% macro consistency in assessing the age of protein-coding genes. Moreover, for the ~5.6% conflicting genes, GageTracker displayed slightly higher support rates than GenTree, as evidenced by data from OrthoDB, FlyBase, and Ensembl ortholog databases. Notably, younger genes identified by GageTracker exhibited a preferential expression pattern in the testis, further reinforcing the reliability of GageTracker in accurately tracing gene age.

bioinformatics↗

bioRxiv2024

Non-destructive in situ monitoring of structural changes of 3D tumor spheroids during the formation, migration, and fusion process

For traditional laboratory microscopy observation, the multi-dimensional, real-time, in situ observation of three-dimensional (3D) tumor spheroids has always been the pain point in cell spheroid observation. In this study, we designed a side-view observation petri dish/device that reflects light, enabling in situ observation of the 3D morphology of cell spheroids using conventional inverted laboratory microscopes. We used a 3D-printed handle and frame to support a first surface mirror, positioning the device within a cell culture petri dish to image cell spheroid samples. The imaging conditions, such as the distance between the mirror and the 3D spheroids, the light source, and the impact of the culture medium, were systematically studied to validate the in-situ side-view observation. The results proved that placing the surface mirror adjacent to the spheroids enables non-destructive in situ real-time tracking of tumor spheroid formation, migration, and fusion dynamics. The correlation between spheroid thickness and dark core appearance under light microscopy and the therapeutic effects of chemotherapy doxorubicin and Natural Killer cells on spheroidss 3D structure was investigated.

cancer biology↗

bioRxiv2024

Cell-Graph Compass: Modeling Single Cells with Graph Structure Foundation Model

Inspired by the advancements in pre-trained Large Language Models, there has been a surge of studies in the Life Sciences focusing on constructing foundation models with large scale single-cell RNA-seq data. These studies typically involve pre-training a transformer model on large-scale single-cell sequencing data, followed by fine-tuning for a variety of downstream tasks, achieving notable performance. However, these models all share a common short-coming: to utilize the transformer architecture, originally designed for textual data, they artificially impose a sequential structure on genes within cells, simplifying the complex interactions between genes. Furthermore, they focus solely on transcriptomic data, neglecting other relevant biological information. To address these issues, here we introduce Cell-Graph Compass (CGC), the first foundational model that leverages graph structures to model single cells and describes cells from multiple perspectives, including transcriptional profiles, gene text summaries, transcription factor regulatory networks, gene co-expression patterns, and gene positional relationships. By incorporating self-attention mechanisms, we pretrained the model on 50 million human single-cell sequencing data, resulting in a robust digital representation of cells. Extensive downstream experiments demonstrate that our approach can capture meaningful biological knowledge and achieve superior results in various problem scenarios, achieving the state-of-the-art (SOTA).

bioinformatics↗

bioRxiv2024

MtrAB two-component system is crucial for the intrinsic resistance and virulence of Mycobacterium abscessus

Mycobacterium abscessus (Mab) poses serious therapeutic challenges, principally due to its intrinsic resistance to a wide array of antibiotics. The pressing issue of drug resistance has spurred an urgent need to explore novel targets and develop new therapeutic agents against Mab. The MtrAB two-component system, conserved among Actinobacteria, is pivotal for regulating various metabolic processes. Nevertheless, the role of MtrAB in Mab remains elusive. In this study, we uncovered that Mab strains with disrupted mtrA, mtrB or both exhibited heightened susceptibility to a variety of antibiotics with diverse mechanisms of action, in contrast to the wild-type strain. In a murine model, rifabutin, bedaquiline, and amikacin, which were inactive against the wild-type Mab strain, demonstrated efficacy against all the mtrA, mtrB and mtrAB knockout strains, significantly reducing pulmonary bacterial burdens compared to vehicle controls after ten days of treatment. Notably, the virulence of all the mtrA, mtrB, and mtrAB knockout strains was highly diminished in the murine model, as evidenced by a substantial decrease in bacterial load in the lungs of mice after 16 days. We observed that all three knockout strains exhibited a significantly reduced growth rate compared to the wild-type strain. We discovered that cells lacking mtrA, mtrB or both exhibited an elongated cell length and had multiple septa, suggesting that both MtrA and MtrB regulate cell division of Mab. Subsequently, an ethidium bromide accumulation assay disclosed that the absence of either mtrA or mtrB or both significantly increased cell envelope permeability. In summary, this study suggests that mtrA and mtrB play an important role in the intrinsic resistance and virulence of Mab by affecting cell division and altering cell permeability. Consequently, MtrA and MtrB represent promising targets for the discovery of anti-Mab drugs. HIGHLIGHTSO_LIKnockout of mtrA, mtrB or mtrAB leads to increased sensitivity of M. abscessus in vitro and in vivo. C_LIO_LIThe mtrA, mtrB or mtrAB knockout M. abscessus strains exhibit highly reduced virulence. C_LIO_LIMtrA and MtrB are potential targets for anti-M. abscessus drug discovery. C_LIO_LIKnockout of mtrA, mtrB or mtrAB results in defective cell division in M. abscessus. C_LI

microbiology↗

bioRxiv2024

How do Large Language Models understand Genes and Cells

Researching genes and their interactions is crucial for deciphering the fundamental laws of biological activity, advancing disease treatment, drug discovery and so on. Large language Models (LLMs), with their profound text comprehension and generation capabilities, have made significant strides across various natural science fields. However, their application in cell biology remains notably scarce. To alleviate this issue, in this paper, we selects seven mainstream LLMs and evaluates their performance across a range of problem scenarios. Our findings indicate that LLMs possess a certain level of understanding of genes and cells, and hold potential for solving real-world problems. Moreover, we have improved the current method of textual representation of cells, enhancing the LLMs ability to tackle cell annotation tasks. We encourage cell biology researchers to leverage LLMs for problem-solving while also being mindful of some challenges associated with their use. We release our code and data at https://github.com/epang-ucas/Evaluate_LLMs_to_Genes. CCS ConceptsApplied computing [->] Recognition of genes and regulatory elements; Bioinformatics; Computational genomics; Computational transcriptomics. ACM Reference FormatChen Fang, Yidong Wang, Yunze Song, Qingqing Long, Wang Lu, Linghui Chen, Pengfei Wang, Guihai Feng, Yuanchun Zhou, and Xin Li. 2024. How do Large Language Models understand Genes and Cells. 1, 1 (March 2024), 14 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn

bioinformatics↗

bioRxiv2024

Decentralizing genetic testing for biodiversity monitoring and biosurveillance with the Nucleic Acid Barcode Identification Tool (NABIT) and Molecular Development Kit (MDK).

O_LIThe escalating threats to biodiversity, public health, and food security posed by emerging infectious diseases and illegal wildlife trafficking requires novel approaches to biosurveillance. This paper introduces two innovations developed to address these multifaceted challenges: the Nucleic Acid Barcode Identification Tool (NABIT) and the Molecular Development Kit (MDK). C_LIO_LIThe NABIT is a handheld, battery-powered device that enables genetic tests to be performed at the point of contact by non-technical users, creating a critical bridge between centralized laboratories and the field by reducing barriers to accessible and routine genetic testing. Verification testing and validation results for the NABIT and the lyophilized assays used with it demonstrate key performance parameters, including sample preparation, detection sensitivity, and stability of field-ready assays after 17 months without refrigeration. C_LIO_LIThe MDK complements the NABIT by providing a framework for third-party development and deployment of field-ready genetic assays. Similar to software development kits (SDKs), the MDK offers documentation, software tools, and NABIT hardware to accelerate the development of new assays, enabling early detection strategies and minimizing future losses. Crucially, the MDK empowers scientists worldwide to contribute to a new ecosystem for wildlife genetics and biosurveillance by developing their own field-ready tests for the NABIT. C_LIO_LIIn summary, the NABIT and MDK present the potential for a paradigm shift in biosurveillance, ecosystem monitoring, and biodiversity conservation, enabling decentralized genetic testing, early disease detection, and rapid response to protect sensitive ecosystems, public health, and food security. C_LI

bioengineering↗

bioRxiv2024

Integrating Knowledge Graphs into Machine Learning Models for Survival Prediction and Biomarker Discovery in Patients with Non-Small-Cell Lung Cancer

Survival prediction is a critical aspect of clinical study design and biomarker discovery. It is a highly complex task, given the large number of "omics" and clinical features, as well as the high degrees of freedom that drive patient survival. Prior knowledge can play a critical role in uncovering the complexity of a disease and understanding the driving factors affecting a patients survival. We introduce a methodology for incorporating prior knowledge into machine learning-based models for prediction of patient survival through knowledge graphs, demonstrating the advantage of such an approach for patients with non-small-cell lung cancer. Using data from patients treated with immuno-oncologic therapies in the POPLAR (NCT01903993) and OAK (NCT02008227) clinical trials, we found that the use of knowledge graphs yielded significantly improved hazard ratios, including in the POPLAR cohort, for models based on biomarker tumor mutation burden compared with those based on knowledge graphs. Use of a model-defined mutational 10-gene signature led to significant overall survival differentiation for both trials. We provide parameterized code for incorporating knowledge graphs into survival analyses for use by the wider scientific community.

bioinformatics↗

bioRxiv2024

Ilamycins are dual inhibitors of ClpX and ClpC1 involved in proteostasis in Mycobacteria

The mycobacterial caseinolytic protease (Clp) system has been recognized as a promising therapeutic target. In this study, we identified two novel ilamycin analogs, ilamycin E (ILE) and ilamycin F (ILF), both targeting the ClpC1 component of the ClpC1P1P2 proteasome. ILE potently disrupts ClpC1P1P2-mediated proteolysis, leading to delayed bactericidal activity, while ILF also binds ClpC1, albeit with lower affinity. Notably, we discovered a unique mutation in clpX and a novel insertion in clpC1, both conferring resistance to ILE and ILF in mycobacterium, validated by gene editing. Furthermore, ILE can also inhibit the proteolytic activity of ClpXP1P2 in a manner dependent on the substrates tag sequence and adaptor. This first demonstration of clpX- and clpC1-mediated ilamycin resistance underscores the potential of ilamycins to target multiple components of the Clp protease system, offering a novel dual-target strategy for combating mycobacterial infections.

microbiology↗

bioRxiv2024

EmbB and EmbC Regulate the Sensitivity of Mycobacterium abscessus to Echinomycin

Treatment of Mycobacterium abscessus (Mab) infection is a major challenge due to its intrinsic resistance to most available drugs. It is thus imperative to find new anti-Mab drugs. In this study, we investigated the activity and intrinsic resistance mechanism of echinomycin (ECH) against Mab. ECH is active against Mab (MIC: 2 {micro}g/mL). The embC gene knockout strain (Mab{Delta}embC) showed hyper-sensitive to ECH (MIC: 0.0078-0.0156 {micro}g/mL). The MICs of ECH-resistant strains screened based on the Mab{Delta}embC strain were 0.25-1 {micro}g/mL. Mutations were found in the EmbB, including Asp306Ala, Asp306Asn, Arg350Gly, Val555Ile, and Gly581Ser, which led to increased resistance to ECH when overexpressed in Mab{Delta}embC individually (0.25-0.5 {micro}g/mL). The EmbB mutants edited by the CRISPR/Cpf1 system became more resistant to ECH (MIC: 0.25-0.5 {micro}g/mL). The permeability of gene-edited and overexpressed Mab strains was reduced, as shown by the ethidium bromide accumulation assay, but it was still significantly higher than that of the parent Mab. To summarize, our study demonstrates that ECH has a strong anti-Mab activity and confirms that EmbB and EmbC are related to the sensitivity of Mab to ECH. EmbB mutation may partially compensate for the function of EmbC. Impact StatementMycobacterium abscessus (Mab) is a rapidly growing, intrinsic multidrug-resistant Mycobacterium. This study demonstrated that echinomycin (ECH) has potent antibacterial activity against Mab, and the mechanism of ECH resistance to Mab is related to EmbB and EmbC. EmbB and EmbC can alter the sensitivity of Mab to ECH by altering the permeability of its cell wall. In addition, there is a functional complementary evolution between EmbB and EmbC to regulate sensitivity to ECH. Overall, our study provides a novel anti-Mab drug candidate ECH and a scientific foundation for developing effective strategies to prevent and control Mab.

microbiology↗

bioRxiv2024

Disrupting Homologous Recombination or Single-Strand Annealing Significantly Hinders CRISPR-Cas12a-Assisted Nonhomologous End-Joining Gene Editing Efficiency in Mycobacterium abscessus

Mycobacterium abscessus, a fast-growing, non-tuberculous mycobacterium resistant to most antimicrobial drugs, causes many types of serious infections in humans, posing a significant public health challenge. Currently, effective genetic manipulation tools for M. abscessus are still being developed, which hampers research and therapeutic development. However, the clustered regularly interspaced short palindromic repeats (CRISPR) - associated protein (Cas) systems have emerged as promising methods for generating highly specific double-strand breaks (DSBs) in its genome. These DSBs can be repaired by the error-prone nonhomologous end joining (NHEJ) mechanism, facilitating targeted gene editing. Here, our study marks a pioneering application of the CRISPR-NHEJ strategy in M. abscessus. Additionally, we discovered that NrgA from Mycobacterium marinum is crucial for the repair of DSBs caused by the CRISPR-Cas system in M. abscessus. Finally, contrary to previous findings, our study also indicates that inhibiting or overexpressing homologous recombination/single-strand annealing significantly decreases the efficiency of NHEJ repair in M. abscessus. This discovery challenges established perspectives and suggests that the NHEJ repair in M. abscessus may require the involvement of components from homologous recombination and single-strand annealing, demonstrating the complex interactions among the three DSB repair pathways in M. abscessus. Impact statementThere are still very few genetic manipulation tools available for Mycobacterium abscessus. Here we report the successful application of CRISPR-Cas12a-assisted nonhomologous end joining (NHEJ) in efficient gene editing in M. abscessus. Contrary to previous research suggesting that homologous recombination (HR) inhibition may enhance such editing efficiency in other Mycobacterium species, our results showed that disruption or overexpression of either HR or single-strand annealing not only failed to enhance but also significantly reduced the gene editing efficiency in M. abscessus. This suggests that NHEJ repair in M. abscessus may require components from both HR and single-strand annealing, highlighting a complex interaction among the DSB repair pathways in M. abscessus.

microbiology↗

bioRxiv2024

Beyond benchmarking: towards predictive models of dataset-specific single-cell RNA-seq pipeline performance

The advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline, including filtering, normalization, and clustering. The large number of methods and their resulting parameter combinations has created a combinatorial set of possible pipelines to analyze scRNA-seq data, which leads to the obvious question: which is best? Several benchmarking studies have sought to compare methods to answer this, but frequently find variable performance depending on dataset and pipeline characteristics. Alternatively, the large number of publicly available scRNA-seq datasets along with advances in supervised machine learning raise a tantalizing possibility: could the optimal pipeline be predicted for a given dataset? Here we begin to answer this question by applying 288 scRNA-seq analysis pipelines to 86 datasets and quantifying pipeline success via a range of measures evaluating cluster purity and biological plausibility. We build supervised machine learning models to predict pipeline success given a range of dataset and pipeline characteristics. We find both that prediction performance is significantly better than random and that in many cases pipelines predicted to perform well provide clustering outputs similar to expert-annotated cell type labels. Finally, we identify characteristics of scRNA-seq datasets that correlate with strong prediction performance that could guide when such prediction models may be useful.

bioinformatics↗

bioRxiv2023

Distinct functions of the kinesin-9 family in mammalian motile cilia

Ciliary beat and intraflagellar transport (IFT) depend on dynein and kinesin motors. Kinesin-9 family members Kif6 and Kif9 are implicated in ciliary motilities across protists and mammals. How they function and whether they act redundantly, however, remain unclear. Here, we show that they play distinct roles in mammals. Kif6 forms puncta that move bidirectionally without or with IFT-B particles along axonemes, whereas Kif9 is immobilized on ciliary central apparatus. Only Kif6 binds to and glides microtubules, and the activities are self-inhibited. Kif6 deficiency in mice impairs directional ciliary beat across ependymal tissues and cerebrospinal fluid flow, resulting in severe hydrocephalus and high mortality, whereas Kif9 deficiency induces mild hydrocephalus without obviously defective ciliary beat and life span. Both Kif6-/- and Kif9-/- males are infertile but show respectively oligozoospermia with poor sperm motility and defective forward motion of sperms. These results suggest Kif6 as a motile cilia-specific IFT motor and Kif9 as a central apparatus regulator.

cell biology↗