Biology subjects

Zhong, C.

Publications and source records attributed to Zhong, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Synthetic ratio computation for programming population composition and multicellular morphology

Recent advancements in genetic engineering have provided diverse tools for artificially synthesizing population diversity in both prokaryotic and eukaryotic systems. However, achieving precise control over the ratios of multiple cell types within a population derived from a single founder remains a significant challenge. In this study, we introduce a suite of recombinase-mediated genetic devices designed to achieve accurate population ratio control, enabling the distribution of distinct functionalities across multiple cell types. We systematically evaluated key parameters influencing recombination efficiency and developed data-driven models to reliably predict binary differentiation outcomes. Using these devices, we implemented parallel and series circuit topologies to create user-defined, complex cell fate branching programs. These branching devices facilitated the autonomous differentiation of precision fermentation consortia from a single founder strain, optimizing cell-type ratios for applications such as pigmentation and cellulose degradation. Beyond biomanufacturing, we engineered multicellular aggregates with genetically encoded morphologies by coordinating self-organization through cell adhesion molecules (CAMs). Our work provides a comprehensive characterization of recombinase-based cell fate branching mechanisms and introduces a novel approach for the bottom-up, high-resolution construction of synthetic consortia and multicellular assemblies.

synthetic biology↗

bioRxiv2024

The mechanism and consequences of amyloid-β modulating thiamine pyrophosphokinase-1 expression in microglia

Ample studies attribute cognitive decline in Alzheimers disease to amyloid-{beta} deposition 1-6. However, brain amyloid-{beta} accumulation that saturates years before the manifestation of clinical symptoms is dissociated with cognitive decline of the disease 7. It is unknown how these two processes are mechanistically linked. In this and our accompanied study, we report that thiamine pyrophosphokinase-1 (TPK) deficiency plays essential roles in both processes via distinct mechanisms. Here we describe that diminished microglia Tpk controls the propagation of amyloid-{beta} plaques. In APP/PS1 transgenic mice, microglia showed elevated Tpk expression at 2-month-old, but reduction in a plaque-centric manner at 8-month-old. Interestingly, lipopolysaccharide, but not amyloid-{beta}, induceed Tpk reduction in cultured microglia. Tpk reduction led to microglia dysfunction, showing volatile motility but reduced phagocytosis and weak response to focal tissue injury, with accumulation of intracellular lipid droplets and abnormal mitochrondria. In Alzheimers disease mice, microglia-specific knockout of Tpk caused diminished plaque coverage, exacerbated plaque burden and synaptic loss. However, increased plaques were not accompanied by the development of neurofibrillary tangles or brain atrophy, in contrast to the phenotype described in our accompanied paper with neuronal Tpk deletion. In conclusion, plaque-induced inflammation reduces Tpk in microglia, selectively exacerbating the spread of amyloid pathology.

neuroscience↗

bioRxiv2024

The Open Pediatric Cancer Project

BackgroundIn 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we present an extension of the OpenPBTA called the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens). FindingsWe utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub), and queryable through PedcBioPortal and the NCIs pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 2021 Central Nervous System Tumor classifications, allowing us to create research-grade integrated diagnoses for these tumors. ConclusionsOpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

genomics↗

bioRxiv2024

A versatile platform for single fluorescent protein-based fluorescence lifetime biosensors

Single fluorescent protein (FP)-based FLIM (fluorescence lifetime imaging) biosensors are potent tools for quantitatively imaging intracellular processes with high spatial and temporal resolution. They only require a single wavelength for detection, which facilitates multi-color imaging. However, the development of single FP-based FLIM biosensors has been limited by the absence of a general design framework and the complexity of the screening process. In this study, we engineered FLIM biosensors capable of detecting ATP (adenosine triphosphate), cAMP (cyclic adenosine monophosphate), citrate, and glucose by inserting each sensing domain into the mTurquoise2 fluorescent protein between Tyr-145 and Phe-146 using peptide linkers. Through efficient linker screening, we successfully developed FLIM biosensors exhibiting an effective dynamic range from 0.5 to 1.0 ns upon analyte binding. This demonstrates that the qmTQ2-ATP-0 backbone is a universal platform for developing mTQ2-based biosensors. As a proof-of-concept, we demonstrated the capabilities of these FLIM biosensors in monitoring the intracellular dynamics of ATP and cAMP alongside dual-color imaging. Therefore, our work presents an accessible methodology for establishing a single FP-based FLIM biosensor platform for quantitative imaging.

molecular biology↗

bioRxiv2024

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

cancer biology↗

bioRxiv2024

Mechanisms mediating arylidene-indolinones induced degradation: thoughts on "Discovery of a Drug-like, Natural Product-Inspired, DCAF11 Ligand Chemotype"

In the recent issue of Nature Communications (2023 Nov 30;14(1):7908), Xue et. al. reported a very interesting and significant discovery of a possible DCAF11 ligand chemotype that could be used as the "warhead" to design bifunctional compounds for targeted degradation via engaging the E3 ligase DCAF11 1 (annotated as ref 1 hereafter). The discovery is of importance to the targeted protein degradation field and was inspired by previous reports suggesting that similar compounds may also engage the autophagosome protein LC3 for degradation and function as autophagy-tethering compounds (ATTECs) 2, 3, 4, 5, 6, 7, which seem to be inconsistent with ref 1. We think that the conclusions based on these data are not necessarily mutually exclusive. After performing additional experiments and analyses, we would like to discuss some possibilities explaining such discrepancies and make a few points of clarification.

biochemistry↗

bioRxiv2024

Mammalian Cell Models of the Distal Convoluted Tubule: A Systematic Review of Cell Lines, Culture Condition and Gene Expression

This review examines the crucial role of human cellular models in renal physiology research, with a specific focus on the distal convoluted tubule (DCT). It aims to provide a comprehensive summary of the origins, culture practices, and genetic studies associated with commonly employed DCT cell models. To achieve this, a systematic literature review was performed on Europe PMC, employing a Boolean search strategy. A total of 6,559 articles were initially screened, resulting in 301 articles on human-origin cell models, 69 on murine models, and 29 on canine models being included in the final analysis. Notably, the review identified two studies that introduced novel immortalised human DCT cell lines developed from primary DCT cells. This paper provides a detailed account of the lineage of each cell model, their prevalent culture conditions, and the frequency and nature of gene transfections--both wild type and mutant--conducted in these models. A significant observation from the analysis was the inconsistent reporting of methodological details across studies, which compromises the reproducibility of the research. Additionally, there was a considerable variation in culture conditions and transfection methods used across different studies. The review also highlights that HEK293 family and murine DCT cell lines do not serve as accurate models for DCT cells, pointing out the frequent need for transfecting DCT-specific genes to simulate DCT functionality adequately. NEW & NOTEWORTHYThis review is the first review to detail the current state of play with cell models of the distal convoluted tubule, including endogenous protein expression, culture conditions etc. We expect this review to be of great utility to established and early career researchers who are interested in nephrological or hypertensive patho/physiology. We have highlighted some important gaps in reporting the established cell models, we think that this kind of review is important for open science.

physiology↗

bioRxiv2024

LncRNA-CIR6 Mediates Repair of Infarcted Hearts by Inducing MSCs Differentiation into Cardiogenic Cells through CDK1

PurposeThis study aims to investigate the induction effect of LncRNA-CIR6 on MSCs differentiation into Cardiogenic Cells in vitro and in vivo. MethodsIn addition to pretreatment with the Ro-3306 (CDK1 inhibitor), LncRNA-CIR6 was transfected into BMSCs and hUCMSCs using jetPRIME. LncRNA-CIR6 was transfected into C57BL/6 mice heart by 100 L of AAV9-cTnT-LncRNA-CIR6-ZsGreen i.v. After 3 weeks of transfection followed by AMI surgery, hUCMSCs (5x105/100 L) were injected by i.v 1 week later. Cardiac function was evaluated using VEVO 2100 and electric mapping 9 days after cell injection. IF, Evans blue-TTC, Masson staining, FACS, and WB were used to determine relevant indicators. ResultsLncRNA-CIR6 induced a significant percentage of differentiation in BMSCs (83.00{+/-}0.58)% and hUCMSCs (95.43{+/-}2.13)% into cardiogenic cells, as determined by the expression of cTnT. Compared with MI group, cardiac contraction and conduction function in MI heart treated by LncRNA-CIR6 or combined with MSCs injection groups were significantly increased as well as the area of MI and fibrosis were significantly lower. The transcriptional expression region of LncRNA-CIR6 was in Chr17 from 80209290 to 80209536. The functional region of LncRNA-CIR6 was located at nucleotides 0-50/190-255 in the sequence. CDK1 is a protein found to be related to the proliferation and differentiation of cardiomyocytes is which located in the functional region of LncRNA-CIR6 secondary structure (from 0 to 17). Ro-3306 impeded the differentiation of MSCs into cardiogenic cells, while MSCs transfected with LncRNA-CIR6 showed high expression of CDK1. LncRNA-CIR6 mediates repair of infarcted hearts by inducing MSCs differentiation into cardiogenic cells through CDK1. ConclusionsLncRNA-CIR6 mediates repair of infarcted hearts by inducing MSCs differentiation into cardiogenic cells through CDK1.

molecular biology↗

bioRxiv2023

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma

Cancer immunotherapies have produced remarkable results in B-cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target. HighlightsO_LIPlasma membrane enriched proteomics defines surfaceome of neuroblastoma C_LIO_LIMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancers C_LIO_LIDLK1 expression is driven by a super-enhancer C_LIO_LIDLK1 silencing in neuroblastoma cells results in cellular differentiation C_LIO_LIADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models C_LI

cancer biology↗

bioRxiv2023

Prominent contributions of selective neuronal subtypes to pediatric drug-resistant focal dysplasia

About 75% cases of epilepsy begin during childhood, and 10 - 30% of pediatric epilepsy patients are resistant to drug treatment. The predominant seizure type in children is focal cortical dysplasia (FCD) which is highly associated with drug-resistant epilepsy, but its underlying cause is poorly understood. We performed single-cell RNA sequencing and patch-clamp recording on fresh brain tissues obtained from pediatric FCD patients shortly after surgery to reveal critical factors contributing to FCD. We report that known epilepsy genes or significant transcriptomic alterations occur in only a few neuronal subgroups, suggesting that epilepsy-associated neurons cluster into only a few neuronal subtypes. These epilepsy-subtypes displayed significant epilepsy-related transcriptomic alterations, especially in the genes associated with excitation/inhibition balance and neuron functional signal pathways. Among eight epilepsy-subtypes, L2_4_CUX2_YWHAH and PVALB_RGS5 subtypes showed the most prominent alterations in FCD patient tissues. Supporting PV-neurons being important, recording from fast-spiking/parvalbumin-containing neurons in acute FCD patient brain slices revealed reduced excitatory synaptic inputs, implicating lower activity in these neurons and fewer synaptic inputs onto them. A higher percentage of mitochondria genes, and likely higher activity in the pathways associated with oxidative phosphorylation and ATP biosynthetic process, was observed in the epilepsy-subtypes, suggesting a high energy expenditure in them. Interestingly, the activity of the above two pathways in most epilepsy-subtypes was lower in the FCD patients, suggesting these subtypes may be more vulnerable to energy deficit in epilepsy. Altogether, transcriptomics is significantly altered in only a few neuronal subtypes in pediatric FCD patient brains. These selective epilepsy-subtypes may play prominent roles in the genesis of pediatric drug-resistant seizure and targeting them may provide new treatment options.

bioinformatics↗

bioRxiv2023

The ChickenGTEx pilot analysis: a reference of regulatory variants across 28 chicken tissues

Chicken is a valuable model for understanding fundamental biology, vertebrate evolution and diseases, as well as a major source of nutrient-dense and lean-protein-enriched food globally. Although it is the first non-mammalian amniote genome to be sequenced, the chicken genome still lacks a systematic characterization of functional impacts of genetic variants. Here, through integrating 7,015 RNA-Seq and 2,869 whole-genome sequence data, the Chicken Genotype- Tissue Expression (ChickenGTEx) project presents the pilot reference of regulatory variants in 28 chicken tissue transcriptomes, including millions of regulatory effects on primary expression (including protein-coding genes, lncRNA and exon) and post-transcriptional modifications (alternative splicing and 3 untranslated region alternative polyadenylation). We explored the tissue-sharing and context-specificity of these regulatory variants, their underlying molecular mechanisms of action, and their utility in interpreting adaptation and genome-wide associations of 108 chicken complex traits. Finally, we illustrated shared and lineage-specific features of gene regulation between chickens and mammals, and demonstrated how the ChickenGTEx resource can further assist with translating genetic findings across species. One-Sentence SummaryThe ChickenGTEx provides a multi-tissue reference of regulatory variants for chicken genetics and genomics, functional genomics, precision breeding, veterinary medicine, vertebrate evolution and even human biomedicine.

genetics↗

bioRxiv2023

Seasonal Variation in Bacterial Community Structures of Mangrove Sediments

Climate change globally and sea level rise affect the mangrove ecosystem. The high diversity and temporal heterogeneity of the mangrove ecosystem will lead to a high diversity of sediment bacterial community structure and function. However, seasonal variations and potential assembly mechanisms of sediment bacterial communities in mangrove ecosystems remain to be discovered. We collected rhizosphere sediments and bulk sediments from Kandelia obovata and Aegiceras corniculatum at three locations covering Dongzhai Harbour in spring, summer, autumn, and winter, and sequenced 16S rRNAs. The results indicated that the alpha and beta diversity of bacterial communities in mangrove sediments differed significantly between seasons, and the bacterial communities in rhizosphere sediments had smaller seasonal changes and were more stable than those in bulk sediment bacterial communities. The seasonal changes in carbon, nitrogen content, and pH were the main influencing factors. The stochastic process dominated the assembly of bacterial communities in mangrove sediments. The assembly of bacterial communities varies between seasons. We found that the proportion of dispersal limitation was significantly negatively correlated with the carbon and nitrogen content in the sediment. Compared with bulk components, the dispersal limitation of bacterial communities in rhizosphere sediments accounted for a lower proportion of community construction, which might be caused by higher carbon and nitrogen content conditions in rhizosphere sediments. We found that beta diversity based on Bray-Curtis distance was significantly positively correlated with dispersal limitation, which explained why the beta diversity of bacterial communities in rhizosphere sediments was significantly lower than that of bulk components. This study increases the understanding of the responses of mangrove bacterial communities to seasonal change and may be beneficial for the protection of mangrove ecosystems in the face of climate change.

ecology↗

bioRxiv2023

Integrated analysis of spatial multi-omics with SpatialGlue

Integration of multiple data modalities in a spatially informed manner remains an unmet need for exploiting spatial multi-omics data. We introduce SpatialGlue, a graph neural network with dual-attention mechanism, to learn each modalitys significance at cross-omics and intra-omics integration. We demonstrate that SpatialGlue can accurately aggregate cell types into spatial domains at a higher resolution on different tissue types and technology platforms, as well as gain insights into cross-modality spatial correlations.

bioinformatics↗

bioRxiv2023

SunTag-PE: a modular prime editing system enables versatile and efficient genome editing

Prime editing (PE) holds tremendous potential in the treatment of genetic diseases because it can install any desired base substitution or local insertion/deletion. However, the full-length PE effector size (6.3-kb) was beyond the packaging capacity of adeno-associated virus (AAV), hindering its clinical transformation. Various splitting strategies have been used to improve its delivery, but always accompanied by compromised PE efficiency. Here, we developed a modular and efficient SunTag-PE system that splits PE effectors into GCN4-nCas9 and single-chain variable fragment (scFv) tethered reverse transcriptase (RT). We observed that SunTag-PEs with 1xGCN4 in the N terminus of nCas9 was the most efficient configuration rather than multiple copies of GCN4. This SunTag-PE strategy achieved editing levels comparable to canonical fused-PE and higher than other split-PE strategies (including sPE and MS2-PE) in both PE2 and PE3 forms with no increase in insertion-deletion (indel) byproducts. Moreover, we successfully validated the modularity of SunTag-PE system in the Cas9 orthologs of SauCas9 and FrCas9. Finally, we employed dual AAVs to deliver SunTag-ePE3 and efficiently corrected the pathogenic mutation in HBB mutant cell line. Collectively, our SunTag-PE system provides an efficient modular splitting strategy for prime editing and further facilitate its transformation in clinics.

bioengineering↗

bioRxiv2022

Dear-DIAXMBD: deep autoencoder for data-independent acquisition proteomics

Data-independent acquisition (DIA) technology for protein identification from mass spectrometry and related algorithms is developing rapidly. The spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition (DDA) data represents a promising direction. In this paper, we proposed an untargeted analysis method, Dear-DIAXMBD, for direct analysis of DIA data. Dear-DIAXMBD first integrates the deep variational autoencoder and triplet loss to learn the representations of the extracted fragment ion chromatograms, then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes, and finally establishes the inverted index tables to determine the precursors of fragment clusters between precursors and peptides, and between fragments and peptides. We show that Dear-DIAXMBD performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms. Dear-DIAXMBD is publicly available at https://github.com/jianweishuai/Dear-DIA-XMBD.

bioinformatics↗

bioRxiv2022

DeepST: A versatile graph contrastive learning framework for spatially informed clustering, integration, and deconvolution of spatial transcriptomics

Advances in spatial transcriptomics technologies have enabled the gene expression profiling of tissues while retaining its spatial context. Effective exploitation of this data combination requires spatially informed analysis tools to perform three key tasks, spatial clustering, multi-sample integration, and cell type deconvolution. Here, we present GraphST, a novel graph self-supervised contrastive learning method that incorporates spatial location information and gene expression profiles to accomplish all three tasks in a streamlined process while outperforming existing methods in each task. GraphST combines graph neural networks with self-supervised contrastive learning to learn informative and discriminative spot representations by minimizing the embedding distance between spatially adjacent spots and vice versa. With GraphST, we achieved 10% higher clustering accuracy on multiple datasets than competing methods, and better delineated the fine-grained structures in tissues such as the brain and embryo. Moreover, GraphST is the only method that can jointly analyze multiple tissue slices in both vertical and horizontal integration while correcting for batch effects. Lastly, compared to other methods, GraphSTs cell type deconvolution achieved higher accuracy on simulated data and better captured spatial niches such as the germinal centers of the lymph node in experimentally acquired data. We further showed that GraphST can recover the immune cell distribution in different regions of breast tumor tissue and reveal spatial niches with exhausted tumor infiltrating T cells. Through our examples, we demonstrated that GraphST is widely applicable to a broad range of tissue types and technology platforms. In summary, GraphST is a streamlined, user friendly and computationally efficient tool for characterizing tissue complexity and gaining biological insights into the spatial organization within tissues.

bioinformatics↗

bioRxiv2021

Combinatorial mRNA vaccination enhances protection against SARS-CoV-2 delta variant

Emergence of SARS-CoV-2 variants of concern (VOC), including the highly transmissible delta strain, has posed challenges to current COVID-19 vaccines that principally target the viral spike protein (S). Here, we report a nucleoside-modified mRNA vaccine that expresses the more conserved viral nucleoprotein (mRNA-N). We show that mRNA-N alone was able to induce a modest but significant control of SARS-CoV-2 in mice and hamsters. Critically, by combining mRNA-N with the clinically approved S-expressing mRNA vaccine (mRNA-S-2P), we found that combinatorial mRNA vaccination (mRNA-S+N) led to markedly enhanced protection against the SARS-CoV-2 delta variant compared to mRNA-S. In a hamster model, we demonstrated that while mRNA-S alone elicited significant control of the delta strain in the lungs ([~]45-fold reduction in viral loads compared to un-vaccinated control), its effectiveness in the upper respiratory tract was weak, whereas combinatorial mRNA-S+N vaccination induced markedly more robust control of the delta variant infection in the lungs ([~]450-fold reduction) as well as in the upper respiratory tract ([~]20-fold reduction). Immune analyses indicated that induction of N-specific immunity as well as augmented S-specific T-cell response and neutralizing antibody activity were collectively associated the enhanced protection against SARS-CoV-2 delta strain by combinatorial mRNA vaccination. These findings suggest that the combined effects of protection in the lungs and upper respiratory tract could both reduce the risk of severe disease as well as of infection and transmission.

microbiology↗

bioRxiv2021

Integrated de novo Gene Prediction and Peptide Assembly of Metagenomic Sequencing Data

Metagenomics is the study of all genomic content presented in given microbial communities. Metagenomic functional analysis aims to quantify protein families and reconstruct metabolic pathways from the metagenome. It plays a central role in understanding the interaction between the microbial community and its host or environment. De novo functional analysis, which allows the discovery of novel protein families, remains challenging for high-complexity communities. There are currently three main approaches for recovering novel genes or proteins: de novo nucleotide assembly, gene calling, and peptide assembly. Unfortunately, their informational connection and dependency have been overlooked, and each has been formulated as an independent problem. In this work, we develop a sophisticated workflow called integrated Metagenomic Protein Predictor (iMPP), which leverages the informational dependencies for better de novo functional analysis. iMPP contains three novel modules: a hybrid assembly graph generation module, a graph-based gene calling module, and a peptide assembly-based refinement module. iMPP significantly improved the existing gene calling sensitivity on unassembled fragmented reads, achieving a 92% - 97% recall rate at a high precision level (>90%). iMPP further allowed for more sensitive and accurate peptide assembly, recovering more reference proteins and delivering more hypothetical protein sequences. The high performance of iMPP can provide a more comprehensive and unbiased view of the microbial communities under investigation. iMPP is freely available from https://github.com/Sirisha-t/iMPP.

bioinformatics↗