Biology subjects

Ni, M.

Publications and source records attributed to Ni, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Predictive power of different Akkermansia phylogroups in clinical response to PD-1 blockade against non-small cell lung cancer

Immune checkpoint blockade has emerged as a promising form of cancer therapy. However, only some patients respond to checkpoint inhibitors, while a significant proportion of patients do not, calling for the discovery of reliable biomarkers. Recent studies reported the importance of the gut microbiome in the clinical response to PD-1 blockade against non-small cell lung cancer (NSCLC), highlighting Akkermansia muciniphila as a candidate biomarker. Motivated by the genomic and phenotypic differences across Akkermansia muciniphila strains and Akkermansia (Akk) phylogroups (AmIa, AmIb, AmII, AmIII and AmIV), we analyzed fecal metagenomic sequencing data from four publicly available NSCLC cohorts (n = 575). Encouragingly, we found that patients responses to PD-1 blockade are significantly different across different Akk phylogroups, highlighting the relatively stronger association between AmIa and positive responses than the other phylogroups. Importantly, we also highlight the importance of considering the clinical heterogeneity among independent cohorts in across validation analysis. We built a machine learning model based on Akk gene profiles, which shed light on a group of Akk genes that may be associated with the response to PD-1 blockade. In summary, our study underlines the benefits of high-resolution analysis of Akk genomes in the search for biomarkers that may improve the prediction of patients responses to cancer immunotherapy.

genomics↗

bioRxiv2024

A single-molecule nanopore sequencing platform

Nanopore sequencing, a third-generation sequencing technology, has revolutionized the gene sequencing industry with its advantages of long reads, fast speed, real-time sequencing and analysis, and potential in detecting base modifications. This technology allows researchers to sequence longer DNA fragments in a single read, providing more comprehensive genomic information compared to previous methods. Nanopore sequencing operates on electrical signals generated by a nanopore embedded in a membrane separating two electrolyte-filled chambers. When single-stranded DNA (ssDNA) passes through the nanopore, it creates variations in the current that correspond to different DNA bases. By analyzing these current fluctuations with machine learning algorithms, the DNA sequence can be determined. In this study, we introduced several improvements to nanopore sequencing, including nanopore local chemistry sequencing, novel motor and pore proteins, chip design, and basecalling algorithms. Our new nanopore sequencing platform, CycloneSEQ, demonstrated long-duration sequencing (107 hours) on a single chip with high yield (>50 Gb). In human genomic DNA sequencing, CycloneSEQ was able to produce long reads with N50 33.6 kb and modal identity 97.0%. Preliminary findings on human whole-genome de novo assembly, variant calling, metagenomics sequencing, and single-cell RNA sequencing have further highlighted CycloneSEQs potential across different areas of genomics.

genomics↗

bioRxiv2024

Optimizing murine sample sizes for RNA-seq studies revealed from large-scale comparative analysis

Determining the appropriate sample size (N) for comparative biological experiments is critical for obtaining reliable results. In order to determine the N, the usual approach is to perform a power calculation, which involves understanding the variability between samples and the expected effect size. Here, we focused on bulk RNA-seq experiments, which have become ubiquitous in biology, but which have many unknown or difficult to estimate parameters, and so the required analyses to determine the minimum N is typically lacking. We therefore performed two N=30 profiling studies between wild-type mice and mice in which one copy of a gene had been deleted, to determine how many mice would be required to minimize false positives and to maximize true discoveries found in the N of 30 experiment. Results from experiments with N=4 or less are shown to be highly misleading, given the substantial false positive rate, and the lack of discovery of genes later found with higher N. For a cut-off of 2-fold expression differences, we found that an N of 6-7 mice was required to consistently decrease the false positive rate to below 50%, and that "more is always better" when it came to discovery rates - an N of 8-12 is significantly better in lowering the false positive rate. A common method to reduce false discovery rate in underpowered experiments is to raise the fold cutoff or increase the stringency of the P-value and include only highly perturbed, highly significant genes. We show that while this strategy is no substitute for increasing the N of the experiment, because it results in consistently inflated effect sizes and a substantial drop in sensitivity. These data should be helpful to others in choosing their Ns, since its often not practical to do such large studies for every mouse model.

bioinformatics↗

bioRxiv2024

Combined aerobic and resistance exercise training alters the spatial transcriptome of skeletal muscle in young adults

Chronic exercise training substantially improves skeletal muscle function and performance. The repeated demands and stressors of each exercise bout drive coordinated molecular adaptations within multiple cell types in muscle tissue, leading to enhanced neuromuscular recruitment and contractile function, stem cell activation, myofiber hypertrophy, mitochondrial biogenesis, and angiogenesis, among others. To comprehensively profile molecular changes induced by combined resistance and endurance exercise training, we employed spatial transcriptomics coupled with immunofluorescence and computational approaches to resolve effects on myofiber and mononuclear cell populations in human muscle. By computationally identifying fast and slow myofibers using immunofluorescence data of spatially sequenced tissue sections, we identified fiber type-specific, exercise-induced gene expression changes that correlated with muscle functional improvements. Additionally, spatial transcriptome profiling and integration of human muscle single cell RNAseq data identified an exercise-induced shift in interstitial cell populations coincident with angiogenesis. Overall, these data provide a unique spatial molecular profiling resource for exploring muscle adaptations to exercise, and provide a pipeline and rationale for future studies in human muscle.

physiology↗

bioRxiv2024

DeepSS2GO: protein function prediction from secondary structure

Predicting protein function is crucial for understanding biological life processes, preventing diseases, and developing new drug targets. In recent years, methods based on sequence, structure, and biological networks for protein function annotation have been extensively researched. Although obtaining a protein in three-dimensional structure through experimental or computational methods enhances the accuracy of function prediction, the sheer volume of proteins sequenced by high-throughput technologies presents a significant challenge. To address this issue, we introduce a deep neural network model DeepSS2GO (Secondary Structure to Gene Ontology). It is a predictor incorporating secondary structure features along with primary sequence and homology information. The algorithm expertly combines the speed of sequence-based information with the accuracy of structure-based features, while streamlining the redundant data in primary sequences and bypassing the timeconsuming challenges of tertiary structure analysis. The results show that the prediction performance surpasses state-ofthe-art algorithms. It has the ability to predict key functions by effectively utilizing secondary structure information, rather than broadly predicting general Gene Ontology terms. Additionally, DeepSS2GO predicts five times faster than advanced algorithms, making it highly applicable to massive sequencing data. The source code and trained models are available at https://github.com/orca233/DeepSS2GO.

bioinformatics↗

bioRxiv2024

HKDC1 Promotes Liver Cancer Stemness Under Hypoxia via Stabilizing β-Catenin

Background and AimsHexokinases (HKs), a group of enzymes catalyzing the first step of glycolysis, have been shown to play important roles in liver metabolism and tumorigenesis. Our recent studies identified HKDC1 as a top candidate associated with liver cancer metastasis. We aimed to compare its cell-type specificity with other HKs upregulated in liver cancer and investigate the molecular mechanisms underlying its involvement in liver cancer metastasis. Approach and ResultsWe found that, compared to HK1 and HK2, the other two commonly upregulated HKs in liver cancer, HKDC1 was most strongly associated with the metastasis potential of tumors and organoids derived from two liver cancer mouse models we previously established. RNA in situ hybridization and single-cell RNA-seq analysis revealed that HKDC1 was specifically upregulated in malignant cells in hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) patient tumors, whereas HK1 and HK2 were widespread across various tumor microenvironment lineages. An unbiased metabolomic profiling demonstrated that HKDC1 overexpression in HCC cells led to metabolic alterations distinct from those from HK1 and HK2 overexpression, with HKDC1 particularly impacting the tricarboxylic acid (TCA) cycle. HKDC1 was prometastatic in HCC orthotopic and tail vein injection mouse models and, molecularly, HKDC1 was induced by hypoxia and bound to glycogen synthase kinase 3{beta} to stabilize {beta}-catenin, leading to enhanced stemness of HCC cells. ConclusionsOverall, our findings underscore HKDC1 as a prometastatic HK specifically expressed in the malignant compartment of primary liver tumors, thereby providing a mechanistic basis for targeting this enzyme in advanced liver cancer.

cancer biology↗

bioRxiv2024

Burkholderia cenocepacia epigenetic regulator M.BceJIV simultaneously engages two DNA recognition sequences for methylation

Burkholderia cenocepacia is an opportunistic and infective bacterium containing an orphan DNA methyltransferase (M.BceJIV) with roles in regulating gene expression and motility of the bacterium. M.BceJIV recognizes a GTWWAC motif (where W can be an adenine or a thymine) and methylates the N6 of the adenine at the fifth base position (GTWWAC). Here, we present a high-resolution crystal structure of M.BceJIV/DNA/sinefungin ternary complex and allied biochemical, computational, and thermodynamic analyses. Remarkably, the structure shows not one, but two DNA substrates bound to the M.BceJIV dimer, wherein each monomer contributes to the recognition of two recognition sequences. This unexpected mode of DNA binding and methylation has not been observed previously and sets a new precedent for a DNA methyltransferase. We also show that methylation at two recognition sequences occurs independently, and that GTWWAC motifs are enriched in intergenic regions of a strain of B. cenocepacias genome. We further computationally assess the interactions underlying the affinities of different ligands (SAM, SAH, and sinefungin) for M.BceJIV, as a step towards developing selective inhibitors for limiting B. cenocepacia infection.

biophysics↗

bioRxiv2023

An interactive web application for exploring human plasma and fibroblast metabolomics data from patients with inborn errors of metabolism

Metabolomic profiling is instrumental in understanding the systemic and cellular impact of inborn errors of metabolism (IEMs), monogenic disorders caused by pathogenic genomic variants in genes involved in metabolism. This study encompasses untargeted metabolomics analysis of plasma from 474 individuals and fibroblasts from 67 subjects, incorporating healthy controls, patients with 65 different monogenic diseases, and numerous undiagnosed cases. We introduce a web application designed for the in-depth exploration of this extensive metabolomics database. The application offers a user-friendly interface for data review, download, and detailed analysis of metabolic deviations linked to IEMs at the level of individual patients or groups of patients with the same diagnosis. It also provides interactive tools for investigating metabolic relationships and offers comparative analyses of plasma and fibroblast profiles. This tool emphasizes the metabolic interplay within and across biological matrices, enriching our understanding of metabolic regulation in health and disease. As a resource, the application provides broad utility in research, offering novel insights into metabolic pathways and their alterations in various disorders.

bioinformatics↗

bioRxiv2023

NASTRA: Innovative Short Tandem Repeat Analysis through Cluster-Based Structure-Aware Algorithm in Nanopore Sequencing Data

Forensic short-tandem repeats (STR) genetic markers are multi-allelic and widely utilized for individual identification, kinship testing, and cell-line authentication. Nanopore sequencing, known for its portability, is emerging as a promising approach for STR typing, facilitating real-time and in-field testing. However, its efficacy is often hampered by sequencing noise. Previous methods rely on alignment-based genotyping, necessitating known alleles, which limits their applicability to unknown alleles. Here, we introduced NASTRA, an innovative allele reference-free tool for precise germline analysis of STR genetic markers. NASTRA incorporates a recursive algorithm to infer repeat structures of allele sequences using only known repeat motifs. Our tests, conducted on 80 individual samples and 8 DNA standards, have demonstrated NASTRAs exceptional 100% accuracy in genotyping nearly all diploid STRs across various multiplex kits and flow cells. It surpasses alignment-based methods in accuracy and speed. In a paternity testing case study, NASTRA accurately identified three relationships among six individuals within an 18-minute sequencing duration. These results underscore NASTRAs ability to perform STR analysis on both NGS and nanopore sequencing platforms, significantly enhancing the utility of nanopore sequencing in relevant applications. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/565630v3_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@296e89org.highwire.dtl.DTLVardef@180b6forg.highwire.dtl.DTLVardef@96bf21org.highwire.dtl.DTLVardef@de1b1d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Lupus IgA1 autoantibodies synergize with IgG to enhance plasmacytoid dendritic cell responses to RNA-containing immune complexes

Autoantibodies to nuclear antigens are hallmarks of the autoimmune disease systemic lupus erythematosus (SLE) where they contribute to pathogenesis. However, there remains a gap in our knowledge regarding how different isotypes of autoantibodies contribute to disease, including the production of the critical type I interferon (IFN) cytokines by plasmacytoid dendritic cells (pDCs) in response to immune complexes (ICs). We focused on IgA, which is the second most prevalent isotype in serum, and along with IgG is deposited in glomeruli in lupus nephritis. Here, we show that individuals with SLE have IgA autoantibodies against most nuclear antigens, correlating with IgG against the same antigen. We investigated whether IgA autoantibodies against a major SLE autoantigen, Smith ribonucleoproteins (Sm/RNPs), play a role in IC activation of pDCs. We found that pDCs express the IgA-specific Fc receptor, FcR, and there was a striking ability of IgA1 autoantibodies to synergize with IgG in RNA-containing ICs to generate robust pDC IFN responses. pDC responses to these ICs required both FcR and Fc{gamma}RIIa, showing a potent synergy between these Fc receptors. Sm/RNP IC binding to and internalization by pDCs were greater when ICs contained both IgA1 and IgG. pDCs from individuals with SLE had higher binding of IgA1-containing ICs and higher expression of FcR than pDCs from healthy control individuals. Whereas pDC FcR expression correlated with blood ISG signature in SLE, TLR7 agonists, but not IFN, upregulated pDC FcR expression in vitro. Together, we show a new mechanism by which IgA1 autoantibodies contribute to SLE pathogenesis. One Sentence SummaryIgA1 autoantibodies synergize with IgG in RNA-containing immune complexes to generate robust pDC IFN responses in a FcR receptor dependent manner.

immunology↗

bioRxiv2023

Electron transport inhibition increases cellular dependence on purine transport and salvage

Cancer cells reprogram their metabolism to support cell growth and proliferation in harsh environments. While many studies have documented the importance of mitochondrial oxidative phosphorylation (OXPHOS) in tumor growth, some cancer cells experience conditions of reduced OXPHOS in vivo and induce alternative metabolic pathways to compensate. To assess how human cells respond to mitochondrial dysfunction, we performed metabolomics in fibroblasts and plasma from patients with inborn errors of mitochondrial metabolism, and in cancer cells subjected to inhibition of the electron transport chain (ETC). All these analyses revealed extensive perturbations in purine-related metabolites; in non-small cell lung cancer (NSCLC) cells, ETC blockade led to purine metabolite accumulation arising from a reduced cytosolic NAD+/NADH ratio (NADH reductive stress). Stable isotope tracing demonstrated that ETC deficiency suppressed de novo purine nucleotide synthesis while enhancing purine salvage. Analysis of NSCLC patients infused with [U-13C]glucose revealed that tumors with markers of low oxidative mitochondrial metabolism exhibited high expression of the purine salvage enzyme HPRT1 and abundant levels of the HPRT1 product inosine monophosphate (IMP). ETC blockade also induced production of ribose-5 phosphate (R5P) by the pentose phosphate pathway (PPP) and import of purine nucleobases. Blocking either HPRT1 or nucleoside transporters sensitized cancer cells to ETC inhibition, and overexpressing nucleoside transporters was sufficient to drive growth of NSCLC xenografts. Collectively, this study mechanistically delineates how cells compensate for suppressed purine metabolism in response to ETC blockade, and uncovers a new metabolic vulnerability in tumors experiencing NADH excess.

biochemistry↗

bioRxiv2023

Clathrin Light Chains are essential in negative regulation of cell death and immunity in Arabidopsis through interacting with autophagy pathway

Clathrin plays a critical role in clathrin-mediated endocytosis (CME) in plants, and it is required for autophagy in mammals. However, the functional interconnection of clathrin with autophagy has not been firmly established in plants. Here, we demonstrate that loss of function of clathrin light chain (CLC) subunit 2 and 3 results in salicylic acid (SA)- and H2O2-dependent accelerated senescence and activated defense responses in Arabidopsis, which are hallmarks of the autophagy-related gene (ATG) mutants. Similar to atg mutants, the clc2-1clc3-1 double mutant has enhanced sensitivity to both carbon and nitrogen starvation and enhanced resistance to biotrophic bacterial and fungal pathogens. In addition, the autophagy flux was significantly reduced in the roots of clc2-1clc3-1 mutant plants relative to Col-0 plants under carbon starvation conditions. Furthermore, our Yeast-2-hybrid (Y2H) and Luciferase complementation assays showed that CLC2 directly interacted with ATG8h and ATG8i. Mutations within the unique ATG8-interacting motif (AIM) of CLC2 as well as at the LIR/AIM-docking site (LDS) of ATG8h abolished the interaction between CLC2 and ATG8h. As anticipated, both GFP-ATG8h/GFP-ATG8i and CLC2 were subjected to autophagic degradation in the vacuoles. Together, our data revealed that the accelerated senescence and activated immune responses observed in Arabidopsis clc2-1clc3-1 mutant plants result from impaired autophagy, and CLC2 participates in autophagy through direct interactions with ATG8h and ATG8i in an AIM1- and LDS-dependent manner. Our results unveil a previously unidentified link between the function of CLCs and autophagy.

plant biology↗

bioRxiv2022

mEnrich-seq: Methylation-guided enrichment sequencing of bacterial taxa of interest from microbiome

Metagenomics has enabled the comprehensive study of microbiomes. However, many applications would benefit from a method that can sequence specific bacterial taxa of interest (pathogens, beneficial microbes, or low-abundance taxa), but not the vast background of other taxa in a microbiome sample. To address this need, we developed mEnrich-seq, a method that can enrich taxa of interest from metagenomic DNA before sequencing. The core idea is to exploit the self vs. non-self genome differentiation provided by natural bacterial DNA methylation and rationally choose methylation-sensitive restriction enzymes (REs), individually or in combination, to deplete host DNA and most background microbial DNA while enriching bacterial taxa of interest. This core idea is integrated with library preparation procedures in a way that only non-digested DNA libraries are sequenced. We performed in-depth evaluations of mEnrich-seq and demonstrated its use in several applications to enrich (up to 117-fold) genomic DNA of pathogenic or beneficial bacteria from human urine and fecal samples, including several species that are hard to culture or of low abundance. We also assessed the broad applicability of mEnrich-seq and found that 3130 (68.03%) of the 4601 strains with mapped methylomes to date can be targeted by at least one commercially available RE, representing 54.78% of the species examined in this analysis. mEnrich-seq provides microbiome researchers with a versatile and cost-effective approach for selective sequencing of diverse taxa of interest directly from the microbiome.

genomics↗

bioRxiv2022

Intratumoral mregDC and CXCL13 T helper niches enable local differentiation of CD8 T cells following PD-1 blockade

Here, we leveraged a large neoadjuvant PD-1 blockade trial in patients with hepatocellular carcinoma (HCC) to search for correlates of response to immune checkpoint blockade (ICB) within T cell-rich tumors. We show that ICB response correlated with the clonal expansion of intratumoral CXCL13+ CH25H+ IL-21+ PD-1+ CD4 T helper cells (CXCL13+ Th) and Granzyme K+ PD-1+ effector-like CD8 T cells, whereas terminally exhausted CD39hi TOXhi PD-1hi CD8 T cells dominated in non-responders. Strikingly, most T cell receptor (TCR) clones that expanded post-treatment were found in pre-treatment biopsies. Notably, PD-1+ TCF-1+ progenitor-like CD8 T cells were present in tumors of responders and non-responders and shared clones mainly with effector-like cells in responders or terminally differentiated cells in non-responders, suggesting that local CD8 T cell differentiation occurs upon ICB. We found that these progenitor CD8 T cells interact with CXCL13+ Th cells within cellular triads around dendritic cells enriched in maturation and regulatory molecules, or "mregDC". Receptor-ligand analysis revealed unique interactions within these triads that may promote the differentiation of progenitor CD8 T cells into effector-like cells upon ICB. These results suggest that discrete intratumoral niches that include mregDC and CXCL13+ Th cells control the differentiation of tumor-specific progenitor CD8 T cell clones in patients treated with ICB.

immunology↗

bioRxiv2021

In vitro and in vivo preclinical studies predict REGEN-COV protection against emergence of viral escape in humans

Monoclonal antibodies against SARS-CoV-2 are a clinically validated therapeutic option against COVID-19. As rapidly emerging virus mutants are becoming the next major concern in the fight against the global pandemic, it is imperative that these therapeutic treatments provide coverage against circulating variants and do not contribute to development of treatment emergent resistance. To this end, we investigated the sequence diversity of the spike protein and monitored emergence of minor virus variants in SARS-COV-2 isolates found in COVID-19 patients or identified from preclinical in vitro and in vivo studies. This study demonstrates that a combination of non-competing antibodies, REGEN-COV, not only provides full coverage against current variants of concern/interest but also protects against emergence of new such variants and their potential seeding into the population in a clinical setting.

microbiology↗

bioRxiv2021

Large field of view-spatially resolved transcriptomics at nanoscale resolution

Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development.

cell biology↗

bioRxiv2020

REGN-COV2 antibody cocktail prevents and treats SARS-CoV-2 infection in rhesus macaques and hamsters

An urgent global quest for effective therapies to prevent and treat COVID-19 disease is ongoing. We previously described REGN-COV2, a cocktail of two potent neutralizing antibodies (REGN10987+REGN10933) targeting non-overlapping epitopes on the SARS-CoV-2 spike protein. In this report, we evaluate the in vivo efficacy of this antibody cocktail in both rhesus macaques and golden hamsters and demonstrate that REGN-COV-2 can greatly reduce virus load in lower and upper airway and decrease virus induced pathological sequalae when administered prophylactically or therapeutically. Our results provide evidence of the therapeutic potential of this antibody cocktail.

microbiology↗

bioRxiv2020

A yeast BiFC-seq method for genome-wide interactome mapping

Genome-wide physical protein-protein interaction (PPI) mapping remains a major challenge for current technologies. Here, we report a high-efficiency yeast bimolecular fluorescence complementation method coupled with next-generation DNA sequencing (BiFC-seq) for interactome mapping. We applied this technology to systematically investigate an intraviral network of Ebola virus (EBOV). Two-thirds (9/13) of known interactions of EBOV were recaptured and five novel interactions were discovered. Next, we used BiFC-seq method to map the interactome of the tumor protein p53. We identified 97 interactors of p53 with more than three quarters are novel. Furthermore, in more complex background, we screened potential interactors by pooling two BiFC-libraries together, and revealing a network of 229 interactions among 205 proteins. These results show that BiFC-seq is a highly sensitive, rapid and economical method in genome-wide interactome mapping.

genomics↗