Biology subjects

Ren, L.

Publications and source records attributed to Ren, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Characterization of Pik1 function in fission yeast reveals its conserved role in lipid synthesis and not cytokinesis

Phosphatidylinositol (PI)-4-phosphate (PI4P) is a lipid found at the plasma membrane (PM) and Golgi in cells from yeast to humans. PI4P is generated from PI by PI4-kinases and can be converted to PI-4,5-bisphosphate [PI(4,5)P2]. Schizosaccharomyces pombe have 2 essential PI4-kinases: Stt4 and Pik1. Stt4 localizes to the PM and its loss from the PM results in a decrease of PM PI4P and PI(4,5)P2. As a result, cells divide non-medially due to disrupted cytokinetic ring-PM anchoring. However, the localization and function of S. pombe Pik1 has not been thoroughly examined. Here, we found that Pik1 localizes exclusively to the trans-Golgi and is required for Golgi PI4P production. We determined that Ncs1 regulates Pik1, but unlike in other organisms, it is not required for Pik1 Golgi localization. When Pik1 function was disrupted, PM PI4P but not PI(4,5)P2 levels were reduced, a major difference with Stt4. We conclude that Stt4 is the chief enzyme responsible for producing the PI4P that generates PI(4,5)P2. Also, that cells with disrupted Pik1 do not divide asymmetrically highlights the specific importance of PM PI(4,5)P2 for cytokinetic ring-PM anchoring. Summary statementFission yeast Pik1 localizes exclusively to the trans-Golgi independently of Ncs1, where it contributes to PI4P but not PI(4,5)P2 synthesis. Pik1 does not affect cytokinesis.

cell biology↗

bioRxiv2023

Deep spatial proteomic exploration of severe COVID-19-related pulmonary injury in post-mortem specimens

The lung, as a primary target of SARS-CoV-2, exhibits heterogeneous microenvironment accompanied by various histopathological changes following virus infection. However, comprehensive insight into the protein basis of COVID-19-related pulmonary injury with spatial resolution is currently deficient. Here, we generated a region-resolved quantitative proteomic atlas of seven major pathological structures within the lungs of COVID-19 victims by integrating histological examination, laser microdissection, and ultrasensitive proteomic technologies. Over 10,000 proteins were quantified across 71 dissected FFPE post-mortem specimens. By comparison with control samples, we identified a spectrum of COVID-19-induced protein and pathway dysregulations in alveolar epithelium, bronchial epithelium, and pulmonary blood vessels, providing evidence for the proliferation of transitional-state pneumocytes. Additionally, we profiled the region-specific proteomes of hallmark COVID-19 pulmonary injuries, including bronchiole mucus plug, pulmonary fibrosis, airspace inflammation, and hyperplastic alveolar type 2 cells. Bioinformatic analysis revealed the enrichment of cell-type and functional markers in these regions (e.g. enriched TGFBI in fibrotic region). Furthermore, we identified the up-regulation of proteins associated with viral entry, host restriction, and inflammatory response in COVID-19 lungs, such as FURIN and HGF. Collectively, this study provides spatial proteomic insights for understanding COVID-19-caused pulmonary injury, and may serve as a valuable reference for improving therapeutic intervention for severe pneumonia.

systems biology↗

bioRxiv2023

Fission yeast CK1 promotes DNA double-strand break repair through both homologous recombination and non-homologous end joining

The CK1 family are conserved serine/threonine kinases with numerous substrates and cellular functions. The fission yeast CK1 orthologues Hhp1 and Hhp2 were first characterized as regulators of DNA repair, but the mechanism(s) by which CK1 activity promotes DNA repair had not been investigated. Here, we found that deleting Hhp1 and Hhp2 or inhibiting CK1 catalytic activities in yeast or in human cells activated the DNA damage checkpoint due to persistent double-strand breaks (DSBs). The primary pathways to repair DSBs, homologous recombination and non-homologous end joining, were both less efficient in cells lacking Hhp1 and Hhp2 activity. In order to understand how Hhp1 and Hhp2 promote DSB repair, we identified new substrates using quantitative phosphoproteomics. We confirmed that Arp8, a component of the INO80 chromatin remodeling complex, is a bona fide substrate of Hhp1 and Hhp2 that is important for DSB repair. Our data suggest that Hhp1 and Hhp2 facilitate DSB repair by phosphorylating multiple substrates, including Arp8.

cell biology↗

bioRxiv2023

Membrane binding of endocytic myosin-1s is inhibited by a class of ankyrin repeat proteins

Myosin-1s are monomeric actin-based motors that function at membranes. Myo1 is the single myosin-1 isoform in Schizosaccharomyces pombe that works redundantly with Wsp1-Vrp1 to activate the Arp2/3 complex for endocytosis. Here, we identified Ank1 as an uncharacterized cytoplasmic Myo1 binding partner. We found that in ank1{Delta} cells, Myo1 dramatically redistributed from endocytic patches to decorate the entire plasma membrane and endocytosis was defective. Biochemical analysis and structural predictions suggested that the Ank1 ankyrin repeats bind the Myo1 lever arm and the Ank1 acidic tail binds the Myo1 TH1 domain to prevent TH1-dependent Myo1 membrane binding. Indeed, Ank1 over-expression precluded Myo1 membrane localization and recombinant Ank1 blocked purified Myo1 liposome binding in vitro. Based on biochemical and cell biology analyses, we propose budding yeast Ank1 and human OSTF1 are functional Ank1 orthologs and that cytoplasmic sequestration by small ankyrin repeat proteins is a conserved mechanism regulating myosin-1s in endocytosis. SummaryFission yeast long-tailed myosin-1 binds Ank1. Ank1 ankyrin repeats associate with the Myo1 lever arm and Ank1 acidic tail binds the Myo1 TH1 domain to inhibit Myo1 membrane binding. Ank1 orthologs exists in budding yeast (Ank1) and humans (OSTF1).

cell biology↗

bioRxiv2022

Mimicking seasonal changes in light-dark cycle and ambient temperature modulates gut microbiome in mice under the same dietary regimen

To better adapt to seasonal environmental changes, physiological processes and behaviors are regulated seasonally. The gut microbiome interacts with the physiology, behavior, and even the diseases of host animals, including humans and livestock. Seasonal changes in gut microbiome composition have been reported in several species under natural environments. Dietary content significantly affects the composition of the microbiome, and, in the natural environment, the diet varies between different seasons. Therefore, understanding the seasonal regulatory mechanisms of the gut microbiome is important for understanding the seasonal adaptation strategies of animals. Herein, we examined the effects of changing day length and temperature, which mimic summer and winter conditions, on the gut microbiome of laboratory mice. Principal coordinate analysis and analysis of the composition of microbiomes of 16S rRNA sequencing data demonstrated that the microbiomes of the cecum and large intestine showed significant differences between summer and winter mimicking conditions. Similar to previous studies, a daily rhythm was observed in the composition of the microbiome. Furthermore, the phylogenetic investigation of communities by reconstruction of unobserved states predicted seasonal changes in several metabolic pathways. Changing day length and temperature can affect the composition of the gut microbiome without changing dietary contents.

physiology↗

bioRxiv2022

Quartet metabolite reference materials for assessing inter-laboratory reliability and data integration of metabolomic profiling

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets. As part of the Quartet Project, we established a publicly available suite of four metabolite reference materials derived from B-lymphoblastoid cell lines from a family quartet of parents and monozygotic twin daughters. We generated comprehensive LC-MS based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. High variabilities in the qualitative and quantitative metabolomic measurements were observed across laboratories. Moreover, the Quartet multi-sample-based quality metrics were developed for objectively assessing the reliability of metabolomic profiling in detecting intrinsic biological differences among difference groups of samples. Importantly, the ratio-based metabolomic profiling, by scaling the absolute values of a study sample relative to those of a universal reference sample, enables data integration in long-term measurements across difference laboratories or platforms. Thus, we constructed the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory proficiency test, which enables objective assessment of various metabolomic methods. Our study provided the community with rich resources and best practice for objective assessment of inter-laboratory measurements and data integration, ensuring reliable large-scale and longitudinal metabolomic profiling.

systems biology↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Correcting batch effects in large-scale multiomic studies using a reference-material-based ratio method

Batch effects are notorious technical variations that are common in multiomic data and may result in misleading outcomes. With the era of big data, tackling batch effects in multiomic integration is urgently needed. As part of the Quartet Project for quality control and data integration of multiomic profiling, we comprehensively assess the performances of seven batch-effect correction algorithms (BECAs) for mitigating the negative impact of batch effects in multiomic datasets, including transcriptomics, proteomics, and metabolomics. Performances are evaluated based on accuracy of identifying differentially expressed features, robustness of predictive models, and the ability of accurately clustering cross-batch samples into their biological sample groups. Ratio-based method is more effective and widely applicable than others, especially in cases when batch effects are highly confounded with biological factors of interests. We further provide practical guidelines for the implementation of ratio-based method using universal reference materials profiled with study samples. Our findings show the promise for eliminating batch effects and enhancing data integration in increasingly large-scale, cross-batch multiomic studies.

systems biology↗

bioRxiv2022

The Quartet Data Portal: integration of community-wide resources for multiomics quality control

The implementation of quality control for multiomic data requires the widespread use of well-characterized reference materials, reference datasets, and related resources. The Quartet Data Portal was built to facilitate community access to such rich resources established in the Quartet Project. A convenient platform is provided for users to request the DNA, RNA, protein, and metabolite reference materials, as well as multi-level datasets generated across omics, platforms, labs, protocols, and batches. Interactive visualization tools are offered to assist users to gain a quick understanding of the reference datasets. Crucially, the Quartet Data Portal continuously collects, evaluates, and integrates the community-generated data of the distributed Quartet multiomic reference materials. In addition, the portal provides analysis pipelines to assess the quality of user-submitted multiomic data. Furthermore, the reference datasets, performance metrics, and analysis pipelines will be improved through periodic review and integration of multiomic data submitted by the community. Effective integration of the evolving technologies via active interactions with the community will help ensure the reliability of multiomics-based biological discoveries. The Quartet Data Portal is accessible at https://chinese-quartet.org. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

systems biology↗

bioRxiv2022

Quartet DNA reference materials and datasets for comprehensively evaluating germline variants calling performance

Current methods for evaluating the accuracy of germline variant calls are restricted to easy-to-detect high-confidence regions, thus ignoring a substantial portion of difficult variants beyond the benchmark regions. We established four DNA reference materials from immortalized cell lines derived from a Chinese Quartet including parents and monozygotic twins. We integrated benchmark calls of 4.2 million small variants and 15,000 structural variants from multiple platforms and bioinformatic pipelines for evaluating the reliability of germline variant calls inside the benchmark regions. The genetic built-in-truth of the Quartet family design not only improved sensitivity of benchmark calls by removing additional false positive variants with apparently high quality, but also enabled estimation of the precision of variants calls outside the benchmark regions. Batch effects of variant calling in large-scale DNA sequencing efforts can be effectively identified with the concurrent use of the Quartet DNA reference materials along with study samples, and can be alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Matched RNA and protein reference materials were also established in the Quartet project, thereby enabling benchmark calls constructed from DNA reference materials for evaluation of variants calling performance on RNA and protein data. The Quartet DNA reference materials from this study are a resource for objective and comprehensive assessment of the accuracy of germline variant calls throughout the whole-genome regions.

bioinformatics↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

bioRxiv2022

Proteomics Characteristics Reveal the Risk of T1 Colorectal Cancer Metastasis to Lymph Nodes

BackgroundThe presence of lymph node metastasis (LNM) affects treatment strategy decisions in T1NxM0 colorectal cancer (CRC), but the currently used clinicopathological-based risk stratification cannot predict LNM accurately. In this study, we established a classifier for predicting LNM in T1 CRC. MethodsWe detected proteins in formalin-fixed paraffin-embedded (FFPE) tumor samples from 143 LNM-negative and 78 LNM-positive patients with T1 CRC and revealed changes in molecular and biological pathways by label-free LC-MS/MS. An effective prediction model was built and validated in a training cohort (N=132) and two validation cohorts (VC1, N=42; VC2, N=47) by machine learning. We further built a simplified classifier with 9 proteins. The expression patterns of 13 proteins were confirmed by immunohistochemistry, and the IHC score of 5 proteins were used to build a IHC predict model. ResultPatients with or without LNM have different molecular signatures. The 55-proteins prediction model achieved an impressive AUC of 1.00 in the training cohort, 0.96 in VC1 and 0.93 in VC2. The 9-protein classifier achieved an AUC of 0.824, and the calibration plot was excellent. We found that 5 biomarkers could predict LNM by the IHC score, with an AUC of 0.825. RHOT2 silence significantly enhanced migration and invasion of colon cancer cells. ConclusionsOur study explored the mechanism of metastasis in T1 CRC and can be used to facilitate the individualized prediction of LNM in patients with T1 CRC, which may provide a guidance for clinical practice in T1 CRC.

cancer biology↗

bioRxiv2022

Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet

As the state-of-the-art sequencing technologies and computational methods enable investigation of challenging regions in the human genome, an update variant benchmark is demanded. Herein, we sequenced a Chinese Quartet, consisting of two monozygotic twin daughters and their biological parents, with multiple advanced sequencing platforms, including Illumina, BGI, PacBio, and Oxford Nanopore Technology. We phased the long reads of the monozygotic twin daughters into paternal and maternal haplotypes using the parent-child genetic map. For each haplotype, we utilized advanced long reads to generate haplotype-resolved assemblies (HRAs) with high accuracy, completeness, and continuity. Based on the ingenious quartet samples, novel computational methods, high-quality sequencing reads, and HRAs, we established a comprehensive variant benchmark, including 3,883,283 SNVs, 859,256 Indels, 9,678 large deletions, 15,324 large insertions, 40 inversions, and 31 complex structural variants shared between the monozygotic twin daughters. In particular, the preciously excluded regions, such as repeat regions and the human leukocyte antigen (HLA) region, were systematically examined. Finally, we illustrated how the sequencing depth correlated with the de novo assembly and variant detection, from which we learned that 30 x HiFi is a balance between performance and cost. In summary, this study provides high-quality haplotype-resolved assemblies and a variant benchmark for two Chinese monozygotic twin samples. The benchmark expanded the regions of the previous report and adapted to the evolving sequencing technologies and computational methods.

genomics↗

bioRxiv2022

The Chromosome-based Genome of Paspalum vaginatum Provides New Insights into Salt-stress Adaptation

Salinization is increasingly a major factor limiting production worldwide. Revealing the mechanism of salt tolerance could help to create salt-tolerant crops and improve their yields. We reported a chromosome-scale genome sequence of the halophyte turfgrass Paspalum vaginatum, and provided structural evidence that it shared a common ancestor with Z. mays and S. bicolor. A total of 107 P. vaginatum germplasms were divided into two groups (China and foreign group) based on the re-sequenced data, and the grouping findings were consistent with the geographical origin. Genome-wide association study (GWAS) of visually scored wilting degree and withering rates identified highly significant QTL on chromosome 6. Combination with RNA-seq, we identified a significantly up-regulated gene under salt stress, which encodes High-affinity K+ Transporter 7 (PvHKT7), as strong candidates underlying the QTL. Overexpression of this gene in Arabidopsis thaliana significantly enhanced salt tolerance by increasing K+ absorption. This study adds new insights into salt-stress adaptation of P. vaginatum and serve as a resource for salt-tolerant improvement of grain crops.

genomics↗

bioRxiv2022

Mechanistic basis for targeting homologous recombination defective liver cancer via synthetic lethality

Many cancers harbour homologous recombination defects (HRD). The identification of PARP inhibitors as synthetic lethal with HRD has led to new therapeutic strategies for HRD cancers. Here we report a subtype of HRD that is caused by the perturbation of a previously uncharacterised proteasome variant, CDW19S, in hepatitis virus B (HBV) positive hepatocellular carcinoma (HBVHCC). CDW19S contains the 19S complex decorated with a Cullin 4 ubiquitin ligase (CRL4WDR70) that is assembled at broken chromatin and regulates end processing nucleases. The HBV oncoprotein, HBx, prevents integration of the CRL4 backbone into CDW19S. We show that CDW19S directly ubiquitinates ADRM1Rpn13, targeting it for degradation, and that HBx interferes with this, leading to the imposition of a novel ADRM1Rpn13-dependent resection barrier that results in HRD and promotes carcinogenesis with concurrent TP53 loss. Using cellular and patient-derived xenograft models we demonstrate that HRD in HBVHCC can be exploited to restrict tumour progression. Our work clarifies the mechanism of a virally-induced HRD and suggests a new route for targeted HBVHCC therapy.

cancer biology↗

bioRxiv2022

Fatty acid binding protein 1 and fatty acid synthetase overexpression have differential effects on collagen III and cross-linking in Zongdihua pig tissues

The purpose of this study was to determine whether FABP1 and FAS regulate expression of collagen and its crosslinking via lysyl oxidase in Zongdihua pigs. We wished to identify processes affecting meat quality using molecular genetics to provide a basis for breeding improvement of these animals. We measured expression levels of FABP1 and related genes using qRT-PCR in longissimus dorsi muscle and subcutaneous adipose tissues. Primary adipocytes from fat tissues were isolated and FABP1 and FAS were overexpressed from recombinant plasmids. Our sequence analysis of the cloned genes indicated that FABP1 gene encodes a hydrophobic protein of 128 amino acids and contained 12 predicted phosphorylation sites and no transmembrane region. FAS encodes 333 amino acid hydrophobic protein containing with 26 phosphorylation sites and 0 transmembrane regions. The basal levels of FABP1 and FAS in pig tissues expression were 3 -3.5-fold higher in subcutaneous fat compared with muscle (P < 0.01). Recombinant expression plasmids were successfully transfected into the cloned preadipocytes and (a) overexpression of FAS resulted in significantly increased expression of COL3A1 gene (P < 0.05) and significantly inhibited lysyl oxidase LOX expression (P < 0.01); (b) overexpression of FABP1 significantly increased COL3A1 expression (P < 0.01) and significantly inhibited LOX expression (P < 0.05) and significantly reduced lysyl oxidase activity (P < 0.01). Therefore, enhancing FABP1 expression increases collagen accumulation and this preliminarily suggests that FAS and FABP1 can serve as fat-related candidate genes providing a theoretical basis for the study of fat deposition in Zongdihua pigs.

animal behavior and cognition↗

bioRxiv2022

The infiltration pattern of microenvironmental cells and different immune escape mechanisms in colorectal cancer

BackgroundThe tumour microenvironment (TME) plays a crucial role in tumour progression and metastasis. However, the infiltration pattern of TME cells in CRC samples and the immune escape mechanism underneath have not been studied sufficiently. MethodsTranscriptomic data from public datasets were retrieved online. In total, 1802 samples from the microarray dataset and 619 samples from the TCGA dataset were enrolled. The ssGSEA algorithm and unsupervised clustering were used for TME cells infiltration speculation and infiltration pattern recognition. ResultsCRC samples can be classified into three distinct TME cell subtypes. Subtype 1, the immune-active subtype, was characterised by high infiltration of activated adaptive immune cells. Subtype 2, the immune-desert subtype, featured high tumour purity and low infiltration of immune and stromal cells. And subtype 3, stroma-rich subtype, had high infiltration of stromal cells. The stroma-rich subtype conferred a significantly worse prognosis. Three subtypes had different immune escape mechanisms. The immune-active subtype has the highest immune checkpoint expression level. In comparison, the immune-desert subtype had the lowest immunogenicity and the defective antigen presentation. And the stroma-rich subtype lacked activated immune cells. ConclusionsDistinct TME cell subtypes and immune escape mechanisms may provide inspiration and direction for further researches on CRC immunotherapy.

cancer biology↗

bioRxiv2021

Natural killer-like B cells promote Th17 cell differentiation and exacerbate rheumatoid arthritis

B cells are important participants in the pathogenesis of rheumatoid arthritis (RA). Besides classical B cells, novel B cell subsets are continually to be identified in recent years. Natural killer-like B (NKB) cells, a newly recognized B cell subset, are proved to be actively involved in the anti-infection immunity. However, their role in RA and the potential mechanism remain elusive. Here, we showed that NKB cells were expanded dramatically in collagen-induced arthritis (CIA) mice, demonstrating dynamic changes during the disease progression. These cells promoted CD4+ effector T cell proliferation and Th17 cell differentiation in vitro, while adoptive transfer of these cells exacerbated the arthritis severity of CIA mice. RNA Sequencing revealed that NKB cells displayed distinct differential gene expression profile under RA circumstance, potential perpetuating the disease progression. Moreover, the frequencies of NKB cells were significantly increased in RA patients, positively correlated with the clinical and immunological features. After effective therapy, these cells could be recovered to normal levels. Taken together, our results preliminarily revealed the pathogenic role of NKB cells in RA by promoting Th17 proinflammatory responses. Targeting these cells might provide potential therapeutic strategies for this persistent disease.

immunology↗