Biology subjects

Peng, B.

Publications and source records attributed to Peng, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Microglia replacement effectively attenuates the disease progress of ALSP in the mouse model and human patient

Microglia play critical roles in the brain physiology and pathology. CSF1R is primarily expressed in microglia. The mono-allelic CSF1R mutation causes adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP), a lethal neurological disease and no rational cure in clinical trials. There are no animal models mimicking human ALSP. In this study, we first developed mouse models based on human ALSP hotspot mutations. We then utilized microglia replacement by bone marrow transplantation (Mr BMT) to replace the Csf1r-deficient microglia in ALSP mice by Csf1r-normal donor cells. With pathogenic gene correction, Mr BMT efficiently attenuated the pathologies. Previously, an ALSP patient received traditional bone marrow transplantation (tBMT) due to a misdiagnosis of metachromatic leukodystrophy. The disease progress was halted for 15 years with unknown reasons. We demonstrated that tBMT in ALSP is equivalent to or close to Mr BMT, achieving efficient microglia replacement and therefore attenuating the ALSP progress in the mouse model. Next, we applied tBMT to replace CSF1R-deficient microglia in human patients. Our clinical results show that after microglia replacement, the ALSP course is effectively halted. Together, microglia replacement corrects the pathogenic gene and thus halts the disease progress in the mouse model and human patients. This study strongly demonstrates clinical potentials of microglia replacement in neurological disease treatments.

neuroscience↗

bioRxiv2024

Intra-amygdala circuits of sleep disruption-induced anxiety in female mice

Combining mouse genetics, electrophysiology, and behavioral training and testing, we explored how sleep disruption may affect the function of anxiety-controlling circuits, focusing on projections from the basolateral nucleus of the amygdala (BLA) to CRF-positive cells in the lateral division of the central amygdala (CeL). We found in Crh-IRES-Cre::Ai14(tdTomato) reporter female mice that 6 hours of sleep disruption during their non-active (light) cycle may be anxiogenic. Notably, the AMPAR/NMDAR EPSC amplitude ratio at the BLA inputs to CRF-CeL cells (CRFCeL), assessed with whole-cell recordings in ex vivo experiments, was enhanced in slices from sleep-disrupted mice, whereas paired-pulse ratio (PPR) of the EPSCs induced by two closely spaced presynaptic stimuli remained unchanged. These findings indicate that sleep disruption-associated synaptic enhancements in glutamatergic projections from the BLA to CRF-CeL neurons may be postsynaptically expressed. We found also that the excitation/inhibition (E/I) ratio in the BLA to CRFCeL inputs was increased in sleep-disrupted mice, suggesting that the functional efficiency of excitation in BLA inputs to CRFCeL cells has increased following sleep disruption, thus resulting in their enhanced activation. The latter could be translated into enhanced anxiogenesis as activation of CRF cells in the CeL was shown to promote anxiety-like behaviors.

neuroscience↗

bioRxiv2024

Discovery of cell type classification marker genes from single cell RNA sequencing data using NS-Forest

The use of single cell/nucleus RNA sequencing (scRNA-seq) technologies that quantitively describe cell transcriptional phenotypes is revolutionizing our understanding of cell biology, leading to new insights in cell type identification, disease mechanisms, and drug development. The tremendous growth in scRNA-seq data has posed new challenges in efficiently characterizing data-driven cell types and identifying quantifiable marker genes for cell type classification. The use of machine learning and explainable artificial intelligence has emerged as an effective approach to study large-scale scRNA-seq data. NS-Forest is a random forest machine learning-based algorithm that aims to provide a scalable data-driven solution to identify minimum combinations of necessary and sufficient marker genes that capture cell type identity with maximum classification accuracy. Here, we describe the latest version, NS-Forest version 4.0 and its companion Python package (https://github.com/JCVenterInstitute/NSForest), with several enhancements to select marker gene combinations that exhibit highly selective expression patterns among closely related cell types and more efficiently perform marker gene selection for large-scale scRNA-seq data atlases with millions of cells. By modularizing the final decision tree step, NS-Forest v4.0 can be used to compare the performance of user-defined marker genes with the NS-Forest computationally-derived marker genes based on the decision tree classifiers. To quantify how well the identified markers exhibit the desired pattern of being exclusively expressed at high levels within their target cell types, we introduce the On-Target Fraction metric that ranges from 0 to 1, with a metric of 1 assigned to markers that are only expressed within their target cell types and not in cells of any other cell types. NS-Forest v4.0 outperforms previous versions on its ability to identify markers with higher On-Target Fraction values for closely related cell types and outperforms other marker gene selection approaches at classification with significantly higher F-beta scores when applied to datasets from three human organs - brain, kidney, and lung.

bioinformatics↗

bioRxiv2024

Deciphering the Immune Subtypes and Signature Genes: A Novel Approach Towards Diagnosing and Prognosticating Severe Asthma through Interpretable Machine Learning.

Asthma, a pervasive pulmonary disorder, affects countless individuals globally. Characterized by chronic inflammation of the bronchial passages, its symptoms include cough, wheezing, dyspnea, and chest tightness. While many manage their symptoms through pharmaceutical interventions and self-care, a significant subset grapples with severe asthma, posing therapeutic challenges. This study delves into the intricate etiology of asthma, emphasizing the pivotal roles of immune cells such as T cells, eosinophils, and mast cells in its pathogenesis. The recent emergence of monoclonal antibodies, including Mepolizumab, Reslizumab, and Benralizumab, offers therapeutic promise, yet their efficacy varies due to the heterogeneous nature of asthma. Recognizing the potential of personalized medicine, this research underscores the need for a comprehensive understanding of asthmas immunological diversity. We employ ssGSEA and LASSO algorithms to identify differentially expressed immune cells and utilize machine learning techniques, including XGBoost and Random Forest, to predict severe asthma outcomes and identify key genes associated with immune cells. Using a murine asthma model and an online database, we aim to elucidate distinct immune-centric asthma subtypes. This study seeks to provide novel insights into the diagnosis and classification of severe asthma through a transcriptomic lens.

bioinformatics↗

bioRxiv2024

msCNVS: medium throughput single cell copy number variation sequencing with barcoded library construction free of preamplification toward clinical implementation

Single cell copy number variation sequencing (scCNV-seq) is valuable for genomic analysis of a variety of health and disease systems, yet the available methods either depend on either preamplification of the whole genome of each cell, special devices or untracable, which hinder scCNV-seq practice in clinics. Here we provide scalable multiplex scCNV-seq (msCNVS) that allows direct medium-throughput library construction for single cells, which are barcoded individually with Tn5 transposome in a microplate and immediately pooled for downstream processes, elevating the efficiency by orders of magnitude. An algorithm is developed on the distribution of segmented normalized read count density to identify the major peaks associating with integer copy numbers, further improving the accuracy for objective CNV calling. Here msCNVS faithfully distinguishes the unique CNV patterns of 5 cell lines. The individual msCNVS profiles of 70 individual K562 cells highly correlate with the profile of K562 bulk cells (R=0.90-0.98), and the triplicates of HeLa3 bulk cells correlated nearly perfect (R=0.99). The msCNVS CNV profiles of primary cell cultures of amniotic fluid are confirmed by G-banding karyotype analysis and chromosomal microarray analysis. Additionally, the coverage uniformity of msCNVS is superior to that of MDA and MALBAC and approaches what eMDA and DOP-PCR achieves. Furthermore, msCNVS detects CNV deletions in 2 stunted, abnormal blastocysts, one with CNV mosaicism, and uncovered variants of CNVs in circulated tumor cells, cancerous pleural effusion cells, and patient-derived xenograft nuclei. Thus, msCNVS promises a robust, reliable and highly efficient approach to genomic testing of precious and rare cells like those typically obtained in reproductive and cancer clinics. One-Sentence SummaryBy early pooling of multiple single cells individually barcoded with Tn5 transposome, msCNVS enables efficient CNV profiling of rare clinic samples

genomics↗

bioRxiv2024

Cyanamide-inducible expression of homing nuclease I-SceI for iterative genome engineering and parallel promoter characterisation in Saccharomyces cerevisiae

In synthetic biology, microbial chasses including yeast Saccharomyces cerevisiae are iteratively engineered with increasing complexity and scale. Wet-lab genetic engineering tools are developed and optimised to facilitate strain construction but are often incompatible with each other due to shared regulatory elements, such as the galactose-inducible (GAL) promoter in S. cerevisiae. Here, we prototyped the cyanamide-induced I-SceI-mediated double-strand DNA breaks (DSBs) for selectable marker recycling in yeast metabolic engineering. We further combined cyanamide-induced I-SceI-mediated DSB and maltose-induced MazF-mediated negative selection for plasmid-free in situ promoter replacement, which simplified the molecular cloning procedure for promoter characterisation in S. cerevisiae. We then characterised three tetracycline-inducible promoters of differential strength, a non-leaky {beta}-estradiol-inducible promoter, cyanamide-inducible DDI2 promoter, bidirectional MAL32/MAL31 promoters, and five pairs of bidirectional GAL1/GAL10 promoters. Overall, alternative regulatory controls for genome engineering tools are important for the construction of complexed genotypes in microbial systems for synthetic biology and metabolic engineering applications.

synthetic biology↗

bioRxiv2024

Genome-wide association study reveals multiple loci for analgesia and heroin taking behavior in outbred rats

The increased prevalence of opioid use disorder (OUD) makes it imperative to disentangle the biological mechanisms contributing to individual differences in OUD vulnerability. OUD shows strong heritability, however genetic variants contributing to vulnerability remain poorly defined. We performed a genome-wide association study using over 850 male and female heterogeneous stock (HS) rats to identify genes underlying behaviors associated with OUD such as nociception, as well as heroin-taking, extinction and seeking behaviors. By using an animal model of OUD, we were able to identify genetic variants associated with distinct OUD behaviors while maintaining a uniform environment, an experimental design not easily achieved in humans. Furthermore, we used a novel non-linear network-based clustering approach to characterize rats based on OUD vulnerability to assess genetic variants associated with OUD susceptibility. Our findings confirm the heritability of several OUD-like behaviors, including OUD susceptibility. Additionally, several genetic variants associated with nociceptive threshold prior to heroin experience, heroin consumption, escalation of intake, and motivation to obtain heroin were identified. Tom1, a microglial component, was implicated for nociception. Several genes involved in dopaminergic signaling, neuroplasticity and substance use disorders, including Brwd1, Pcp4, Phb1l2 and Mmp15 were implicated for the heroin traits. Additionally, an OUD vulnerable phenotype was associated with genetic variants for consumption and break point, suggesting a specific genetic contribution for OUD-like traits contributing to vulnerability. Together, these findings identify novel genetic markers related to the susceptibility to OUD-relevant behaviors in HS rats.

genetics↗

bioRxiv2024

ProT-Diff: A Modularized and Efficient Approach to De Novo Generation of Antimicrobial Peptide Sequences through Integration of Protein Language Model and Diffusion Model

Antimicrobial Peptides (AMPs) represent a promising class of antimicrobial agents crucial for combating antibiotic-resistant pathogens. Despite the emergence of deep learning approaches for AMP discovery, there remains a gap in efficiently generating novel AMPs across various amino acid lengths without prior knowledge of peptide structures or sequence alignments. Here we introduce ProT-Diff, a modularized and efficient deep generative approach that ingeniously combines a pre-trained protein language model with a diffusion model to de novo generate candidate AMP sequences. ProT-Diff enabled the rapid generation of thousands of AMPs with diverse lengths within hours. Following in silico screening based on physicochemical properties and predicted antimicrobial activities, we selected 35 peptides for experimental validation. Remarkably, 34 of these peptides demonstrated antimicrobial activity against Gram-positive or Gram-negative bacteria, with 6 exhibiting broad-spectrum efficacy. Of particular interest, AMP_2, one of the broad-spectrum peptides, displayed potent antimicrobial activity, low hemolysis, and minimal cytotoxicity. Further in vivo assessment revealed its high effectiveness against a clinically relevant drug-resistant E. coli strain in a mouse model of acute peritonitis. This study not only presents a viable generative strategy for novel AMP design but also underscores its potential for generating other functional peptides, thereby broadening the horizon for new drug development.

synthetic biology↗

bioRxiv2024

The integration of tandem gene repeats via a bacterial type-II toxin-antitoxin-mediated gene amplification (ToxAmp) system and stability visualisation in Saccharomyces cerevisiae

Tandem gene repeats naturally occur as important genomic features and determine many traits in living organisms, like human diseases and microbial productivities of target bioproducts. Here, we develop a bacterial type-II toxin-antitoxin-mediated method to manipulate genomic integration of tandem gene repeats in Saccharomyces cerevisiae and further visualise the evolutionary trajectories of gene repeats. We designed a tri-vector system to introduce toxin-antitoxin-driven gene amplification (ToxAmp) modules, and accidentally re-visited the high-level capacity of multi-fragment co-transformation in S. cerevisiae. This system delivered the multi-copy gene integration in the form of tandem gene repeats spontaneously and independently from toxin-antitoxin-mediated selection. Inducing the toxin (RelE) expressing via a copper (II)-inducible CUP1 promoter successfully drove the in-situ gene amplification of the antitoxin (RelB) module, resulting in [~]40 copies of a green fluorescence reporter (GFP) gene per copy of genome. The copy-number changes, increasing and decreasing, and stable maintenance were visualised using the GFP and blue chromoprotein AeBlue as reporters. Copy-number increasing happened spontaneously not depending on a selection pressure and was quickly enriched through toxin-antitoxin-mediated selection. In summary, the bacterial toxin-antitoxin systems provide a flexible mechanism to manipulate gene copy number in eukaryotic cells and can be exploited for synthetic biology and metabolic engineering applications. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/578080v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@75d1f3org.highwire.dtl.DTLVardef@12aafeforg.highwire.dtl.DTLVardef@184a1a5org.highwire.dtl.DTLVardef@90586a_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Enhancing radiotherapy response via intratumoral injection of the TLR9 agonist CpG to stimulate CD8 T cells in an autochthonous mouse model of sarcoma

Radiation therapy is frequently used to treat cancers including soft tissue sarcomas. Prior studies established that the toll-like receptor 9 (TLR9) agonist cytosine-phosphate-guanine oligodeoxynucleotide (CpG) enhances the response to radiation therapy (RT) in transplanted tumors, but the mechanism(s) remain unclear. Here, we used CRISPR/Cas9 and the chemical carcinogen 3-methylcholanthrene (MCA) to generate autochthonous soft tissue sarcomas with high tumor mutation burden. Treatment with a single fraction of 20 Gy RT and two doses of CpG significantly enhanced tumor response, which was abrogated by genetic or immunodepletion of CD8+ T cells. To characterize the immune response to RT + CpG, we performed bulk RNA-seq, single-cell RNA-seq, and mass cytometry. Sarcomas treated with 20 Gy and CpG demonstrated increased CD8 T cells expressing markers associated with activation and proliferation, such as Granzyme B, Ki-67, and interferon-{gamma}. CpG + RT also upregulated antigen presentation pathways on myeloid cells. Furthermore, in sarcomas treated with CpG + RT, TCR clonality analysis suggests an increase in clonal T-cell dominance. Collectively, these findings demonstrate that RT + CpG significantly delays tumor growth in a CD8 T cell-dependent manner. These results provide a strong rationale for clinical trials evaluating CpG or other TLR9 agonists with RT in patients with soft tissue sarcoma.

cancer biology↗

bioRxiv2023

coRIC map: a framework for the exploration of multifaceted subcellular RNA-binding proteins

The ability of RNA-binding proteins (RBPs) to form complexes with other biomolecules underpins a broad range of functions and remarkable structural properties. Understanding the precise spatiotemporal dynamics of RBPs and their interacting partners in the steady state and upon perturbation is key to deciphering these aspects. Here, we present the coRIC (compartmentalized RNA Interactome Capture) map, an experimental resource and analytical pipeline to study the subcellular dynamics of RBPs through multimodal dataset integration and machine learning. Using this approach, we have generated an atlas comprising 1,768 RBPs distributed in a broad panel of subcellular compartments and delineated their intermolecular and intercompartmental relationships. We have also defined the hierarchy of RBP-containing complexes at multiple scales across the cell, uncovering previously unknown functions of multiple RBPs. Furthermore, we have investigated the changes in RBP complex composition and subcellular distribution in response to C9ORF72 amyotrophic lateral sclerosis/frontotemporal dementia dipeptide repeats and DNA damage stress. The coRIC map provides a valuable new approach for defining the roles of RBPs in homeostasis and disease.

cell biology↗

bioRxiv2023

Microglia facilitate and stabilize the response to general anesthesia

General anesthesia leads to a loss of consciousness and an unarousable state in patients. Although general anesthetics are widely used in clinical practice, their underlying mechanisms remain elusive. The potential involvement of nonneuronal cells is unknown. Microglia are important immune cells in the central nervous system (CNS) that play critical roles in CNS function and dysfunction. We unintentionally observed delayed anesthesia induction and early anesthesia emergence in microglia-depleted mice. We found that microglial depletion differentially regulates neuronal activities by suppressing the neuronal network of anesthesia-activated brain regions and activating emergence-activated brain regions. Thus, microglia facilitate and stabilize the anesthesia status. This influence is not mediated by dendritic spine plasticity. Instead, it relies on the activation of microglial P2Y12 and subsequent calcium influx, which facilitates the general anesthesia response. Together, we elucidate the regulatory role of microglia in general anesthesia, extending our knowledge of how nonneuronal cells modulate neuronal activities.

neuroscience↗

bioRxiv2023

Grain Utilization by the Gut Microbiome as a Human Health Phenotype to Identify Multiple Effect Loci in Genome-Wide Association Studies of Sorghum bicolor

A growing epidemic of complex lifestyle diseases such as obesity and metabolic diseases are explained in part by dysbiosis of the human gut microbiome. The gut microbiome, comprising trillions of microorganisms, contributes to functions ranging from digestion to the immune system. Diet plays a critical role in determining the species composition and functionality of the gut microbiome. Substantial functional metabolic diversity exists within the cultivated grain crops which directly or indirectly provide more than half of all calories consumed by humans around the globe, however much of this diversity is poorly characterized and the effects of such diversity on the human gut microbiome is not well studied. We employed a quantitative genetics approach to identify genetic variants in sorghum that alter the composition and function of human gut microbes. Using an automated high-throughput phenotyping method based on in vitro microbiome fermentation of grain from a diverse population of Sorghum bicolor cultivars, we demonstrate sorghum genetics can explain effects of grain variation on fermentation patterns of bacterial taxa across multiple human microbiomes. In a genome-wide analysis using a sorghum association panel, we identified fifteen multiple-effect loci (MEL) where different alleles in the sorghum genome produced changes in seed that affect the abundance of multiple bacterial taxa across two human microbiomes in automated in vitro fermentations. In a number of cases parallel genome-wide association studies conducted for biochemical and agronomic traits identified seed traits potentially causal for the link between sorghum genetics and human microbiome outcomes. This work demonstrates that genetic factors affecting sorghum seed can drive significant effects on human gut microbes, particularly bacterial taxa considered beneficial. Understanding these relationships will enable targeted crop breeding strategies to improve human health through gut microbiome modulation.

genomics↗

bioRxiv2023

Heterologous naringenin production in the filamentous fungus Penicillium rubens

Naringenin is a natural product with several reported bioactivities and is the key intermediate for the entire class of plant flavonoids. The translation of flavonoids into modern medicine as pure compounds is often hampered by their low abundance in nature and difficult chemical synthesis. Here, we investigated new avenues toward producing high levels of naringenin in microbial hosts. Penicillium rubens is a well characterized and highly engineered traditional "workhorse" for the production of {beta}-lactam antibiotics and cholesterol-lowering statins. We explored a secondary metabolite deficient P. rubens strain, P. rubens 4xKO, that was derived from an earlier industrial production strain as a promising microbial host for a recombinant flavonoid pathway. By integrating two plant genes encoding for enzymes in the naringenin biosynthesis pathway into the genome of this strain, we achieved a high naringenin titer in flask fermentations 36 h after feeding the precursor p-coumaric acid. Along with the rapid product accumulation of up to an 88% molar yield, we also observed rapid degradation of naringenin. Based on high-resolution mass spectrometric analysis, we identified the degradation products and proposed a naringenin degradation pathway in P. rubens 4xKO, which is distinct from other flavonoid-converting pathways reported in fungi. Our approach combines fundamental research with application-oriented microbial engineering, and our findings will pave the way to the more sustainable and economically feasible production of flavonoids for pharmaceutical and nutraceutical applications.

biochemistry↗

bioRxiv2023

ULK1-dependent phosphorylation of PKM2 antagonizes O-GlcNAcylation and inhibits the Warburg effect in breast cancer

Pyruvate kinase M2 (PKM2) is a central metabolic enzyme driving the Warburg effect in tumor growth. Previous investigations have demonstrated that PKM2 is subject to O-linked {beta}-N-acetylglucosamine (O-GlcNAc) modification, which is a nutrient-sensitive post-translational modification. Here we found that unc-51 like autophagy activating kinase 1 (ULK1), a glucose-sensitive kinase, interacts with PKM2 and phosphorylates PKM2 at Ser333. Ser333 phosphorylation antagonizes PKM2 O-GlcNAcylation, promotes its tetramer formation and enzymatic activity, and decreases its nuclear localization. By downregulating glucose consumption and lactate production, PKM2 pS333 attenuates the Warburg effect. Through mouse xenograft assays, we demonstrate that the phospho-deficient PKM2-S333A mutant promotes tumor growth in vivo. In conclusion, we identified a ULK1-PKM2-c-Myc axis in inhibiting breast cancer, and a glucose-sensitive phosphorylation of PKM2 in modulating the Warburg effect.

biochemistry↗

bioRxiv2023

High dimensional analyses reveal activation of lymphocyte subsets and reversal of immunoresistance by cytokine enhancement of adoptive cellular vaccine therapy in prostate cancer.

Engineered cell therapies have emerged as a potent therapeutic option for the hematologic malignancies, however solid tumor responses to similar approaches have been modest. The outlier is Sipuleucel-T (sip-T), an FDA-approved autologous cellular immunotherapy for metastatic castration-resistant prostate cancer (mCRPC). To elucidate parameters of the response profile to this therapy, we report the first high dimensional cellular analyses of sip-T using mass cytometry (CyTOF) and show a lymphoid predominance, with CD3+ T cells constituting the highest proportion (median [~]60%) of sip-T, followed by B-cells, and natural killer (NK) and NKT cells. We hypothesized that treatment of sip-T with homeostatic cytokines known to activate/expand effector lymphocytes could augment efficacy against prostate cancer. Of cytokines tested, IL-15 treated sip-T showed the most significant activation and proliferation of effector lymphocytes, as well as augmentation of tumor cytotoxicity in vitro. Co-culture of sip-T with IL-15 and control or prostate-relevant antigens showed significant activation and expansion of CD8 T and NKT cells in an antigen-specific manner. Adoptive transfer of IL-15 treated sip-T into NSG mice resulted in potent prostate tumor growth inhibition compared with control sip-T. Evaluation of tumor-infiltrating lymphocytes revealed a 2 to 14-fold higher influx of sip-T and a significant increase in interferon (IFN)-{gamma} producing CD8+ T and NKT cells within the tumor microenvironment (TME) in the IL-15 group. In conclusion, we put forward the first evidence that IL-15 treatment can enhance the functional anti-tumor efficacy of sip-T, providing rationale for combining IL-15 or IL-15 agonists with sip-T to treat mCRPC patients. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/550213v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@130adb0org.highwire.dtl.DTLVardef@db2567org.highwire.dtl.DTLVardef@174a953org.highwire.dtl.DTLVardef@18c049_HPS_FORMAT_FIGEXP M_FIG C_FIG One sentence summaryIL-15 treatment can enhance the efficacy/anti-tumor immunity of sipuleucel-T by modulating CD8+ T-cell and CD56+ NKT subsets.

immunology↗

bioRxiv2023

How much storage precision can be lost: Guidance for near-lossless compression of untargeted metabolomics mass spectrometry data

The size of high-resolution mass spectrometry (HRMS) data has been increasing significantly. Several lossy compressors have been developed for higher compression rates. Currently, a comprehensive evaluation of what and how MS data (m/z and intensities) with precision losses would affect data processing (i.e., feature detection and compound identification) is absent. Here, we set an error threshold at 1% to assess the significance of the difference between two files in feature and compound detection results obtained from MZmine3. First, we examined that mzML files with both m/z and intensity encoded in 32-bit precision appear to be a preferred combination via msConvert, which has smaller file size and minor variation with other combinations of storage precision (<0.13%). We then identified that the absolute error of 10-4 for m/z had a feature detection error of 0.57% and compound detection error of 1.1%. For intensities, the relative error group of 2x10-2 had an error of 4.65% for features and 0.98% for compounds, compared with precision-lossless files. Taken together, we provided a reasonable scene-accuracy proposal, with a maximum absolute error of 10-4 for m/z and a maximum relative error of 2x10-2 for intensity. This guidance aimed to help researchers in improving lossy compression algorithms and minimizing the negative effects of precision losses on downstream data processing.

bioinformatics↗

bioRxiv2023

Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level

Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically very heterogenous. To unravel phenotypically relevant MB subtypes, we compiled a harmonized proteome dataset of 167 MBs and integrated findings with DNA methylation and N-glycome data. Six proteome MB subtypes emerged, that could be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pGroup3-Myc), and synapses/immunological processes (pSHHs, pGroup3 and pGroup4). Multiomic analysis revealed different conservation levels of proteome features across MB subtypes at the DNA-methylation level. Aggressive pGroup3-Myc MBs and favorable pWNT MBs were most similar in cluster hierarchies concerning overall proteome patterns but showed different protein abundances of the vincristine resistance associated multiprotein complex TriC/CCT and of N-glycan turnover associated factors. The N-glycome reflected proteome subtypes and complex-bisecting N-glycans characterized pGroup3-Myc tumors. Our results shed light on new targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures. SignificanceWhereas the application of omics technologies has significantly improved MB tumor classification and treatment stratification, it is still of debate, which features predict best clinical outcome. Moreover, treatment options - especially for high-risk groups - are still unsatisfactory. In contrast to nucleic acids, the proteome and their N-glycans may reflect the phenotype of a tumor in a more direct way and thus hold the potential to discover clinically relevant phenotypes and potentially targetable pathways. We show that these analyses are feasible on formalin fixed and paraffine embedded tissue. Compiling a comprehensive MB dataset, we detected new biomarkers and characteristics for high- and low-risk MB subtypes that were not reflected by other omic data modalities before. Specifically, we identified subtype specific abundance differences in proteins of the vincristine resistance associated multiprotein complex TriC/CCT and in proteins involved in N-glycan turnover. Changes in the N-glycans are considered as potential hallmarks of cancer and we show that N-glycan profiles can distinguish MB subtypes. These tumor-specific N-glycan structures hold a strong potential as new biomarkers, as well as immunotherapy targets. Highlights- Integration of in-house proteome data on formalin fixated paraffine embedded medulloblastoma (MB) and publicly available datasets enables large scale proteome analysis of MB - Six proteome MB subtypes can be assigned to two main molecular programs: replication/ translation versus synapse/immune system - Identification and validation of IHC compatible protein-biomarkers for high and low risk MB subtypes, such as TNC and PALMD. - Subtype specific correlation of the DNA methylome and the proteome reveals different conserved molecular characteristics across MB subtypes. - pGroup3-Myc subtype MBs are associated with high-risk features including high abundances of vincristine resistance associated TriC/CCT member proteins - Proteome MB subtypes show differential N-glycosylation patterns, revealing complex-bisecting glycans as potentially immunotargetable hallmarks of the high risk pGroup3-Myc subtype.

cancer biology↗