Biology subjects

Feng, C.

Publications and source records attributed to Feng, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

A humanized 16A antibody conjugated with DNA topoisomerase I inhibitors, targeting a GSTA glycosite-signature epitope.

BackgroundWe previously reported the 16A antibody, which binds to the abnormally glycosylated tandem repeat region of the MUC1 glycoprotein, and developed 16A-MMAE as an antibody-drug conjugate. However, its antitumor efficacy as an antibody-drug conjugate with DNA topoisomerase Iinhibitors remains unknown. MethodsWe humanized the 16A antibody and conjugated it to DXd and MF6, two DNA topoisomerase I inhibitors. The antitumor efficacy of the conjugates was evaluated in vitro and in vivo. ResultsThe humanized 16A-DXd conjugate showed potent antitumoral efficacy, with an IC50 in the nM range against CFPAC1 cells. In vivo, h16A-DXd and h16A-MF6 inhibited tumor growth in asubcutaneous mouse tumor transplantation model using CT26-COSMC KO-hMUC1 cells, administered at a dose of 10 mg/kg. ConclusionsThe high antitumor efficacy of h16A-conjugated DNA topoisomerase I inhibitors supports further clinical development. The relatively low toxicity of h16A-DXd and h16A-MF6 may enable a higher therapeutic window, since MUC1-positive cells internalize the antibody-drug conjugate more efficiently.

pharmacology and toxicology↗

bioRxiv2025

Improved Prediction of Bacterial Type VI Secretion Effector Proteins Using an Integrated Convolutional Neural Network Model Combining N-terminal Signal Sequences, Evolutionary Information and Pre-Trained Protein Language Features

Type VI secretion system effectors (T6SEs) are crucial for bacterial pathogenicity, making their accurate identification essential for understanding bacterial virulence mechanisms. This study analyzed the differences in amino acid composition of N-terminal signal sequences between T6SEs and non-T6SEs, uncovering distinct positional amino acid preferences in T6SEs. Using a combination of unsupervised and supervised analysis, we evaluated feature encoding methods and developed T6CNN, an ensemble model that integrates N-terminal signal sequences, evolutionary information, and pre-trained protein language features for T6SE prediction. T6CNN demonstrated outstanding performance in independent testing, outperforming existing tools with a 7.9% accuracy increase (to 0.953), a 13.2% sensitivity improvement (to 0.964), and a 6.6% specificity enhancement (to 0.951). The T6CNN model offers a reliable and accurate solution for T6SE prediction, with significant potential to advance research on bacterial pathogenicity. ImportanceThis study introduces T6CNN, a new computational model for identifying Type VI secretion system effectors used by harmful bacteria. By analyzing early protein sequences, T6CNN uncovers unique features that reliably distinguish effector proteins. Integrating evolutionary data and pre-trained protein language features, the model outperforms existing methods in accuracy, sensitivity, and specificity. This enhanced prediction tool deepens our understanding of bacterial infection mechanisms and offers researchers a valuable resource for pinpointing key virulence factors. Ultimately, T6CNN may help drive the development of more targeted antibacterial treatments and strategies to combat bacterial diseases.

bioinformatics↗

bioRxiv2025

The neuron-intrinsic membrane skeleton is required for motor neuron integrity throughout lifespan

Axons experience physical stress throughout an organisms lifetime, and disruptions in axonal integrity are hallmarks of both neurodegenerative diseases and traumatic injuries. The spectrin-based membrane periodic skeleton (MPS) is proposed to have a crucial role in maintaining axonal strength, flexibility, and resilience. To investigate the importance of the intrinsic MPS for GABAergic motor neuron integrity in C. elegans, we employed the auxin-inducible degron system to degrade {beta}-spectrin/UNC-70 in a cell-type specific and time-dependent manner. Degradation of {beta}-spectrin from all neurons beginning at larval development resulted in widespread axon breakage and regeneration in VD/DD GABAergic motor neurons in both larval and adult animals. Similarly, targeted degradation of {beta}-spectrin in GABA neurons alone resulted in extensive breakage. Moreover, we found that depleting {beta}-spectrin from the mature nervous system also induced axon breaks. By contrast, epidermal {beta}-spectrin was not required for axon integrity of VD/DD neurons. These findings demonstrate the cell-intrinsic importance of neuronal {beta}-spectrin/UNC-70 for axon integrity both during development and in adulthood.

neuroscience↗

bioRxiv2024

Phosphotyrosine Signal Profiling of Clinical CAR-T Reveals Tonic Signaling Associated with Therapeutic Efficacy

Chimeric Antigen Receptor T (CAR-T) therapies have revolutionized the treatment of cancers such as relapsed and refractory B cell malignancies. However, the precise therapeutic mechanism of CAR-T action remain to be elucidated. In this study, we systematically analyzed CAR signaling via phosphotyrosine (pTyr) proteomics in CAR-T cells from both clinical patients and healthy donors. We found that CAR-T products from clinical patients displayed heightened tyrosine phosphorylation, particularly in the JAK-STAT, MAPK and TCR signaling cascades. We also identified the significantly regulated pTyr sites in primary CAR-T cells under tonic signaling or upon stimulation by antigen-presenting CD19-K562 cells. Although both CD28{zeta} and 4-1BB{zeta} CAR-T cells exhibited comparable pTyr changes, CD28{zeta} CAR-T cells displayed a more pronounced activation in the TCR signaling pathway. Additionally, comparative analysis between clinical and primary CAR-T cells suggested that CAR-T products were subject to heightened tonic signaling, which may be related to therapeutic relapse. Our findings reveal the state of clinical CAR-T products and refine the CAR-T signal transduction network, providing comprehensive insights and informed guidance for CAR-T therapies.

immunology↗

bioRxiv2024

A genome-scale single cell CRISPRi map of trans gene regulation across human pluripotent stem cell lines

Population-scale resources of genetic, molecular, and cellular information form the basis for understanding human genomes, charting the heritable basis of disease, and tracing the effects of mutations. Pooled perturbation assays applied to cellular models, probing the effect of many perturbations coupled with an scRNA-seq readout (Perturb-seq), are especially potent references for interpreting disease-linked mutations or gene expression changes. However, the utility of existing maps has been limited by the comprehensiveness of perturbations possible, and the relevance of their cell line context. Here, we present the first genome-scale CRISPR interference (CRISPRi) perturbation map with single-cell RNA sequencing readout across many human genetic backgrounds in human pluripotent cells. To do so, we establish large-scale CRISPRi screening in human induced pluripotent stem cells from healthy donors, using over 20,000 guide RNAs to target 7,226 genes across 34 cell lines from 26 genetic backgrounds, and gather expression data from nearly 2 million cells. We comprehensively map trans expression changes induced by the target knockdowns, which complement co-expression patterns in unperturbed cells and facilitate the functional annotation of target genes to biological processes and complexes. Consistency of targeting protein complex members point to protein complexes as a nexus for aggregating transcriptional variation, revealing novel interaction partners. We characterise variation in perturbation effects across donors, with expression quantitative trait loci linked to higher genetic modulation of perturbation effects but overall low replication of trans effects due to knockdown of their corresponding cis regulators. This study pioneers population-scale CRISPR perturbations with single cell readouts that will fuel foundation models for the future of effective modulation of cellular disease phenotypes.

genetics↗

bioRxiv2024

Chemosensory modulation of eye-body coordination in larval zebrafish

Coordinated eye-body movements are essential for adaptive behavior, yet little is known about how multisensory input, particularly chemosensory cues, shapes this coordination. Using our enhanced Fish-on-Chips optofluidic platform, we uncovered complex dynamics in how larval zebrafish coordinate saccadic eye movements with tail flips. Under baseline conditions, spontaneous tail flips dynamically align with saccades in frequency and direction for coordinated turns. Chemosensory valence further modulates this coordination: death-associated cues intensify both the strength and relative frequency of coupled saccade-tail flips during turns, whereas food-related cues promote forward gliding without altering saccade coupling. Concurrent brain-wide neuronal imaging reveals that the zebrafish pallium represents the mapping between aversive valence and enhanced saccade-tail coordination, with stronger coupling associated with higher pallium activation. These findings uncover the neural representations and behavioral strategies by which chemosensory inputs of different valences are associated with amplified eye-body coordination and adaptive locomotion in a developing vertebrate, offering insights into principles of sensory-motor integration.

neuroscience↗

bioRxiv2024

Benchmarking alternative polyadenylation detection in single-cell and spatial transcriptomes

Background3-tag-based sequencing methods have become the predominant approach for single-cell and spatial transcriptomics, with some protocols proven effective in detecting alternative polyadenylation (APA). While numerous computational tools have been developed for APA detection from these sequencing data, the absence of comprehensive benchmarks and the diversity of sequencing protocols and tools make it challenging to select appropriate methods for APA analysis in these contexts. ResultsWe systematically compared seven 3-tag-based sequencing protocols and identified key peak features affecting APA detection performance. We developed a simulation pipeline that generates realistic datasets preserving protocol-specific characteristics. Using simulated and real data, we comprehensively assessed six computational tools for their ability to identify polyA sites, quantify polyA site expression, detect differentially expressed (DE) APA genes, filter sequencing artifacts, and their computational efficiency. We also investigated factors influencing APA detection. Our evaluation revealed that SCAPE and scAPAtrap generally outperformed other tools across various performance metrics and protocols. ConclusionOur systematic evaluation provides guidance for tool selection, experiment design, and future tool development in APA analysis for singlecell and spatial transcriptomics, paving the way for investigating APA in these contexts.

bioinformatics↗

bioRxiv2024

A highly adaptable protocol for mapping spatial features of cellular aggregates in tissues

Multiplex imaging technologies have developed rapidly over the past decades. The advancement of multiplex imaging has been driven in part by the recognition the spatial organisation of cells can represent important prognostic biomarkers and that simply studying the composition of cells in diseased tissue is often insufficient. There remains a lack of tools that can perform spatial analysis at the level of cellular aggregates (a common histopathological presentation) such as tumors and granulomas, with most analysis packages focussing on smaller regions of interest and potentially missing patterns in the overall lesion structure and cellular distribution. Here we present a protocol to quantify the cellular structure of entire tissue lesions built around two novel metrics. The Total Cell Preference Index reports whether a lesion tends to change in density in its central vs peripheral areas and can indicate the extent of necrosis across the entire lesion. The Immune Cell Preference Index then reports whether each immune cell-type is located more centrally or peripherally across the entire lesion. The output of both indexes is a single number readout for simple interpretation and visualization, and they can be applied to lesions of any size or shape. Additionally, this protocol can be applied to any slide-scanning multiplexed imaging system, either based on protein and nucleic acid staining. Finally, the protocol uses the open-source software QuPath and can be utilized by researchers with a basic understanding of QuPath with the full protocol able to be applied on pre-generated images within one hour.

immunology↗

bioRxiv2024

Towards a Taxonomy Machine. A Training Set of 5.6 Million Arthropod Images

The taxonomic identification of organisms from images is an active research area within the machine learning community. Current algorithms are very effective for object recognition and discrimination, but they require extensive training datasets to generate reliable assignments. This study releases 5.6 million images with representatives from 10 arthropod classes and 26 insect orders. All images were taken using a Keyence VHX-7000 Digital Microscope system with an automatic stage to permit high-resolution (4K) microphotography. Providing phenotypic data for 324,000 species derived from 48 countries, this release represents, by far, the largest dataset of standardized arthropod images. As such, this dataset is well suited for testing the efficacy of machine learning algorithms for identifying specimens to higher taxonomic categories.

bioinformatics↗

bioRxiv2024

Origin and stepwise improvement of vertebrate lungs

Lungs, essential for terrestrial vertebrates and present in bony fishes but absent in cartilaginous fishes, provide an ideal model for studying organ origination. Our study analyzed single-cell RNA sequencing data from mature and developing vertebrate lungs, revealing substantial similarities in cell composition, developmental trajectories and gene expression pattern across species. Notably, most lung-related genes are also present in cartilaginous fishes, indicating that gene presence alone does not guarantee lung development. We identified thousands of lung regulatory elements specific to bony fishes, with higher concentrations around genes such as tbx4 and the hoxb gene cluster. These regulatory changes might contribute to lung emergence as well as the unique co-expression patterns in lung epithelial cells, such as those related to pulmonary surfactants and cell morphology. Our research also revealed that AT1 cells are specific to mammals, and we identified a mammal-specific gene, sfta2. Knockout experiments demonstrated that sfta2 deletion causes severe respiratory defects in mice, underscoring its critical role in specialized mammalian lungs. In conclusion, our results demonstrate that the origin and evolution of lungs are driven by a complex interplay of regulatory network modifications and the emergence of new genes, underscoring the multifaceted nature of organ evolution.

evolutionary biology↗

bioRxiv2024

Genomic and Genetic Insights into Mendel's Pea Genes

Pea, Pisum sativum, is an excellent model system through which Gregor Mendel established the foundational principles of inheritance. Surprisingly, till today, the molecular nature of the genetic differences underlying the seven pairs of contrasting traits that Mendel studied in detail remains partially understood. Here, we present a genomic and phenotypic variation map, coupled with haplotype-phenotype association analyses across a wide range of traits in a global Pisum diversity panel. We focus on a genomics-enabled genetic dissection of each of the seven traits Mendel studied, revealing many previously undescribed alleles for the four characterized genes, R, Le, I and A, and elucidating the gene identities and mutations for the remaining three uncharacterized traits. Notably, we identify: (1) a ca. 100kb deletion upstream of the Chlorophyll synthase (ChlG) gene, which generates aberrant transcripts and confers the yellow pod phenotype of gp mutants; (2) an in-frame premature stop codon mutation in a Dodeca-CLE41/44 signalling peptide which explains the parchmentless mutant phenotype corresponding to p; and (3) a 5bp in-frame deletion in a CIK-like receptor kinase gene corresponding to the fasciated stem phenotype fa, which Mendel described in terms of flower position, and we postulate the existence of a Modifier of fa (Mfa) locus that masks this meristem defect. Mendel noted the pleiotropy of the a mutation, including inhibition of axil ring anthocyanin pigmentation, a trait we found to be controlled by allelic variants of the gene D within an R2R3-MYB gene cluster. Furthermore, we characterize and validate natural variation of a quantitative genetic locus governing both pod width and seed weight, characters that Mendel deemed were not sufficiently demarcated for his analyses. This study establishes a cornerstone for fundamental research, education in biology and genetics, and pea breeding practices.

genetics↗

bioRxiv2024

From gene to structure: Unraveling genomic dark matter in Ca. Accumulibacter

Candidatus Accumulibacter is a unique and pivotal genus of polyphosphate-accumulating organisms (PAOs) prevalent in wastewater treatment plants, and plays mainstay roles in the global phosphorus cycle. Whereas, the efforts toward a complete understanding of their genetic and metabolic characteristics are largely hindered by major limitations in existing sequence-based annotation methods, leaving more than half of their protein-encoding genes unannotated. To address the challenge, we developed a comprehensive approach integrating pangenome analysis, gene-based protein structure and function prediction, and metatranscriptomic analysis, extending beyond the constraints of sequence-centric methodologies. The application to Ca. Accumulibacter allowed the establishment of the pan-Ca. Accumulibacter proteome structure database, providing references for >200,000 proteins. Benchmarking on 28 Ca. Accumulibacter genomes showed major increases in the average annotation coverage from 51% to 83%. Genetic and metabolic characteristics that had eluded exploration via conventional methods were unraveled. For instance, the identification of a previously unknown phosphofructokinase gene suggests that all Ca. Accumulibacter encoded a complete Embden-Meyerhof-Parnas pathway. A previously defined homolog of phosphate-specific transport system accessory protein (PhoU) was actually an inorganic phosphate transport (Pit) accessory protein, regulating Pit instead of the high-affinity phosphate transport (Pst), a key to the emergence of the polyphosphate-accumulating trait of Ca. Accumulibacter. Additional lineage members were found encoding complete denitrification pathways. This study offers a readily usable and transferable tool for the establishment of high-coverage annotation reference databases for diverse cultured and uncultured bacteria, facilitating the exploration and understanding of genomic dark matter in the bacterial domain. SynopsisA integrated and advanced approach unraveling key genomic dark matter in Ca. Accumulibacter and readily applicable to diverse bacteria for customerized high-coverage annotation reference database establishment

genomics↗

bioRxiv2023

INTEGRATED GLOBAL CHICKEN REFERENCE PANEL FROM 13,187 CHICKEN GENOMES

Chickens are a crucial source of protein for humans and a popular model animal for bird research. Despite the emergence of imputation as a reliable genotyping strategy for large populations, the lack of a high-quality chicken reference panel has hindered progress in chicken genome research. To address this issue, here we introduce the first phase of the 100 K Global Chicken Reference Panel Project (100 K GCRPP). The project includes 13,187 samples and provides services for varied applications on its website (http://farmrefpanel.com/GCRP/). Currently, two panels are available: a Comprehensive Mix Panel (CMP) for domestication diversity research and a Commercial Breed Panel (CBP) for breeding broilers specifically. Evaluation of genotype imputation quality showed that CMP had the highest imputation accuracy compared to imputation using existing chicken panel in animal SNPAtlas, whereas CBP performed stably in the imputation of commercial populations. Additionally, we found that genome-wide association studies using GCRP-imputed data, whether on simulated or real phenotypes, exhibited greater statistical power. In conclusion, our study indicates that the GCRP effectively fills the gap in high-quality reference panels for chickens, providing an effective imputation platform for future genetic and breeding research.

bioinformatics↗

bioRxiv2023

Development of a Next Generation SNP Genotyping Array for Wheat

High throughput genotyping arrays have provided a cost effective, reliable and interoperable system for genotyping hexaploid wheat and its related germplasm pool. Existing, highly cited arrays including our 35K Axiom Wheat Breeders genotyping array and the Illumina 90K iSelect array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in sequencing wheat varieties and landraces has given us access to a vast pool of SNP diversity, whilst technological improvements in array design has allowed us to fit significantly more probes onto a 384-well format Axiom array than was previously possible. Here we describe a novel High Density Axiom genotyping array, the Triticum aestivum Next Generation array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins "Core Collection". We use a novel "minimal marker" optimisation approach to select up to six SNPs in each 1.5 MB region of the wheat genome with the highest combined varietal discrimination potential. A design iteration step allowed us to test and replace skim-sequence derived SNPs which failed to convert to reliable Axiom markers, resulting in a final design, designated TaNG1.1 with 43,372 SNPs derived from a haplotype-optimised combination of novel SNPs, DArTAG-derived and legacy wheat Axiom markers. We show that this design has an even distribution of SNPs across chromosomes and sub-genomes compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous Axiom array. We also demonstrate the improved performance of TaNG1.1 for Genome Wide Association Studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available, and the marker annotations, initial genotyping results and software used to generate the optimised marker sets are freely available.

genomics↗

bioRxiv2023

Investigation of contributions from cortical and subcortical brain structures for speech decoding

Language impairments often arise from severe neurological disorders, prompting the development of neural prosthetics based on electrophysiological signals for the restoration of comprehensible language information. Previous decoding efforts have focused mainly on signals from the cerebral cortex, neglecting the potential contributions of subcortical brain structures to speech decoding in brain-computer interfaces (BCIs). This study aims to explore the role of subcortical structures for speech decoding by utilizing stereotactic electroencephalography (sEEG). Two native Mandarin Chinese speakers, who underwent sEEG implantation for pharmaco-resistant epilepsy, participated in this study. sEEG contacts were primarily located in the superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, thalamus, hippocampus, insular gyrus, amygdala, and parahippocampal gyrus. The participants were asked to read Chinese text, which included 407 Chinese characters (covering all Chinese syllables), displayed on a screen after receiving prompts. 1-30, 30-70 and 70-150 Hz frequency band powers of sEEG signals were used as key features. A deep learning model based on long short-term memory (LSTM) was developed to evaluate the contribution of different brain structures during encoding of speech. Prediction of speech characteristics of consonants (articulatory place and manner) and tone within single words based on the selected features and electrode contact locations was made. Cortical signals were generally better at articulatory place prediction (86.5% accuracy, chance level = 12.5%), while cortical and subcortical signals predicted articulatory manner at similar level (51.5% vs 51.7% accuracy, respectively, chance level = 14.3%). Subcortical signals generated better prediction for tone (around 58.3% accuracy, chance level = 25%). Superior temporal gyrus remains highly relevant during speech decoding for both consonants and tone. Prediction reached the highest level when cortical and subcortical inputs were combined, especially for tone prediction. Our findings indicate that both cortical and subcortical structures can play crucial roles for speech decoding, each contributing to different aspects of speech.

neuroscience↗

bioRxiv2023

A high-performance brain-sentence communication designed for logosyllabic language

Many severe neurological diseases, such as stroke and amyotrophic lateral sclerosis, can impair or destroy the ability of verbal communication. Recent advances in brain-computer interfaces (BCIs) have shown promise in restoring communication by decoding neural signals related to speech or motor activities into text. Existing research on speech neuroprosthesis has predominantly focused on alphabetic languages, leaving a significant gap of logosyllabic languages such as Mandarin Chinese which are spoken by more than 15% of the world population. Logosyllabic languages pose unique challenges to brain-to-text decoding due to extended character sets (e.g., 50,000+ for Mandarin Chinese) and complex mapping between characters and pronunciation. To address these challenges, we established a speech BCI designed for Mandarin, decoding speech-related stereoelectroencephalography (sEEG) signals into coherent sentences. We leverage the unique acoustic features of Mandarin Chinese syllables, constructing prediction models for syllable components (initials, tones, and finals), and employ a language model to resolve pronunciation to character ambiguities according to the semantic context. This method leads to a high-performance decoder with a median character accuracy of 71.00% over the full character set, demonstrating huge potentials for clinical application. To our knowledge, we are the first to report brain-to-sentence decoding for logosyllabic languages over full character set with a large intracranial electroencephalography dataset.

neuroscience↗

bioRxiv2023

Unveiling the A-to-I mRNA editing machinery and its regulation and evolution in fungi

A-to-I mRNA editing occurs during fungal sexual reproduction with an unknown mechanism. Here, we demonstrated that the eukaryotic tRNA-specific heterodimeric deaminase FgTad2-FgTad3, not typically associated with mRNA editing, is responsible for A-to-I mRNA editing in Fusarium graminearum. This editing capacity relies on the interaction between FgTad3 and a sexual stage-specific protein called Ame1. The interaction emerged in Sordariomycetes. Key residues involved in the interaction have been identified. Expression and activity of FgTad2-FgTad3 are regulated through alternative promoters, alternative translation initiation, and post-translational modifications. FgTad2-FgTad3-Ame1 efficiently edits target mRNAs in yeasts, bacteria, and human cells, with significant implications for developing base editors in therapy and agriculture. This study reveals mechanisms, regulation, and evolution of RNA editing in fungi, emphasizing protein-protein interactions in controlling enzyme function.

molecular biology↗

bioRxiv2023

Harnessing Landrace Diversity Empowers Wheat Breeding for Climate Resilience

Breeding crops resilient to climate change is urgently needed to help ensure food security. A key challenge is to harness genetic diversity to optimise adaptation, yield, stress resilience and nutrition. We examined the genetic and phenotypic diversity of the A.E. Watkins landrace collection of bread wheat (Triticum aestivum), a major global cereal, through whole-genome re-sequencing (827 Watkins landraces and 208 modern cultivars) and in-depth field evaluation spanning a decade. We discovered that modern cultivars are derived from just two of the seven ancestral groups of wheat, leaving five groups as previously untapped sources for breeding. This provides access to landrace-specific functional variations using structured germplasm, genotyping and informatics resources. Employing complementary genetic populations and approaches, we identified thousands of high-resolution quantitative trait loci (QTL) and significant marker-trait associations for major traits, revealing many Watkins-unique loci that can confer superior traits in modern wheat. Furthermore, we identified and functionally verified causative genes for climate-change adaptation, nutritional enhancement and resistance to wheat blast. Finally, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritised QTL in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilising genetic diversity in crop improvement to achieve sustainable food security.

plant biology↗