Biology subjects

Gong, M.

Publications and source records attributed to Gong, M..

47 records · Page 3Linked to original sources

bioRxiv2020

Mucin-type O-glycosylation Landscapes of SARS-CoV-2 Spike Proteins

The densely glycosylated spike (S) proteins that are highly exposed on the surface of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) facilitate viral attachment, entry, and membrane fusion. We have previously reported all the 22 N-glycosites and site-specific N-glycans in the S protein protomer. Herein, we report the comprehensive and precise site-specific O-glycosylation landscapes of SARS-CoV-2 S proteins, which were characterized using high-resolution mass spectrometry. Following digestion using trypsin and trypsin/Glu-C, and de-N-glycosylation using PNGase F, we determined the mucin-type (GalNAc-type) O-glycosylation pattern of S proteins, including unambiguous O-glycosites and the 6 most common O-glycans occupying them, via Byonic identification and manual validation. Finally, 43 O-glycosites were identified in the insect cell-expressed S protein. Most glycosites were modified by non-sialylated O-glycans such as HexNAc(1) and HexNAc(1)Hex(1). In contrast, 30 O-glycosites were identified in the human cell-expressed S protein S1 subunit. Most glycosites were modified by sialylated O-glycans such as HexNAc(1)Hex(1)NeuAc(1) and HexNAc(1)Hex(1)NeuAc(2). Our results are the first to reveal that the SARS-CoV-2 S protein is a mucin-type glycoprotein; clustered O-glycans often occur in the N- and the C-termini of the S protein, and the O-glycosite and O-glycan compositions vary with the host cell type. These site-specific O-glycosylation landscapes of the SARS-CoV-2 S protein are expected to provide novel insights into the viral binding mechanism and present a strategy for the development of vaccines and targeted drugs.

biochemistry↗

bioRxiv2020

Efficient and stable metabarcoding sequencing from DNBSEQ-G400 sequencer examined by large fungal community analysis

ABSTRACTMetabarcoding has become the de facto method for characterizing the structure of microbial communities in complex environmental samples. To determine how sequencing platform may influence microbial community characterization, we present a large-scale comparison of two sequencing platforms; Illumina MiSeq and a new platform DNBSEQ-G400 developed by MGI Tech. The accuracy of DNBSEQ-G400 on bacterial and fungal mock samples and compared sequencing consistency and precision between DNBSEQ-G400 and MiSeq platforms by sequencing the fungal ITS2 region from 1144 soil samples with 3 technical replicates. The DNBSEQ-G400 showed a high accuracy in reproducing mock communities containing different proportions of bacteria and fungi, respectively. The taxonomic profiles of the 1144 soil samples generated by the two DNBSEQ-G400 modes closely resembled each other and were highly correlated with those generated by the MiSeq platform. Analyses of technical replicates demonstrated a run bias against certain taxa on the MiSeq but not DNBSEQ-G400 platform. Based on lower cost, greater capacity, and less bias, we conclude that DNBSEQ-G400 is an optimal platform for short-term metabarcoding of microbial communities.IMPORTANCE Experimental steps that generate sequencing bias during amplicon sequencing have been intensively evaluated, including the choice of primer pair, polymerase, PCR cycle and technical replication. However, few studies have assessed the accuracy and precision of different sequencing platforms. Here, we compared the performance of newly released DNBSEQ-G400 sequencer with that of the commonly used Illumina MiSeq platform by leveraging amplicon sequencing of a large number of soil samples. Significant sequencing bias among major fungal genera was found in parallel MiSeq runs, which can be easily neglected without the use of sequencing controls. We emphasize the importance of technical controls in large-scale sequencing efforts and provide DNBSEQ-G400 as an alternative with increased sequencing capacity and more stable reproducibility for amplicon sequencing.View Full Text

microbiology↗

bioRxiv2020

Functional and Genetic Analysis of Viral Receptor ACE2 Orthologs Reveals Broad Potential Host Range of SARS-CoV-2

The pandemic of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major global health threat. Epidemiological studies suggest that bats are the natural zoonotic reservoir for SARS-CoV-2. However, the host range of SARS-CoV-2 and intermediate hosts that facilitate its transmission to humans remain unknown. The interaction of coronavirus with its host receptor is a key genetic determinant of host range and cross-species transmission. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) as the receptor to enter host cells in a species-dependent manner. It has been shown that human, palm civet, pig and bat ACE2 can support virus entry, while the murine ortholog cannot. In this study, we characterized the ability of ACE2 from diverse species to support viral entry. We found that ACE2 is expressed in a wide range of species, with especially high conservation in mammals. By analyzing amino acid residues of ACE2 critical for virus entry, based on structure of SARS-CoV spike protein interaction with human, bat, palm civet, pig and ferret ACE2, we identified approximately eighty ACE2 proteins from mammals that could potentially mediate SARS-CoV-2 entry. We chose 48 representative ACE2 orthologs among eighty orthologs for functional analysis and it showed that 44 of these mammalian ACE2 orthologs, including those of domestic animals, pets, livestock, and animals commonly found in zoos and aquaria, could bind SARS-CoV-2 spike protein and support viral entry. In contrast, New World monkey ACE2 orthologs could not bind SARS-CoV-2 spike protein and support viral entry. We further identified the genetic determinant of New World monkey ACE2 that restricts viral entry using genetic and functional analyses. In summary, our study demonstrates that ACE2 from a remarkably broad range of species can facilitate SARS-CoV-2 entry. These findings highlight a potentially broad host tropism of SARS-CoV-2 and suggest that SARS-CoV-2 might be distributed much more widely than previously recognized, underscoring the necessity to monitor susceptible hosts to prevent future outbreaks.

microbiology↗

bioRxiv2020

Site-specific N-glycosylation Characterization of Recombinant SARS-CoV-2 Spike Proteins using High-Resolution Mass Spectrometry

SummaryThe glycoprotein spike (S) on the surface of SARS-CoV-2 is a determinant for viral invasion and host immune response. Herein, we characterized the site-specific N-glycosylation of S protein at the level of intact glycopeptides. All 22 potential N-glycosites were identified in the S-protein protomer and were found to be preserved among the 753 SARS-CoV-2 genome sequences. The glycosites exhibited glycoform heterogeneity as expected for a human cell-expressed protein subunits. We identified masses that correspond to 157 N-glycans, primarily of the complex type. In contrast, the insect cell-expressed S protein contained 38 N-glycans, primarily of the high-mannose type. Our results revealed that the glycan types were highly determined by the differential processing of N-glycans among human and insect cells. This N-glycosylation landscape and the differential N-glycan patterns among distinct host cells are expected to shed light on the infection mechanism and present a positive view for the development of vaccines and targeted drugs.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsACE2angiotensin-converting enzyme IICryo-EMcryoelectron microscopyEenvelope proteinHCoV-NL63human coronavirus NL63Mmembrane proteinMSmass spectrometryMERS-CoVMiddle East respiratory syndrome coronavirusNnucleocapsid proteinRBDreceptor-binding domainSspike proteinSARS-CoV-2severe acute respiratory syndrome coronavirusSCEstepped collision energyZic-HILICzwitterionic hydrophilic interaction liquid chromatographyView Full Text

biochemistry↗

bioRxiv2020

CoolMPS™: Advanced massively parallel sequencing using antibodies specific to each natural nucleobase

Massively parallel sequencing (MPS) on DNA nanoarrays provides billions of reads at relatively low cost and enables a multitude of genomic applications. Further improvement in read length, sequence quality and cost reduction will enable more affordable and accurate comprehensive health monitoring tests. Currently the most efficient MPS uses dye-labeled reversibly terminated nucleotides (RTs) that are expensive to make and challenging to incorporate. Furthermore, a part of the dye-linker (scar) remains on the nucleobase after cleavage and interferes with subsequent sequencing cycles. We describe here the development of a novel MPS chemistry (CoolMPS) utilizing unlabeled RTs and four natural nucleobase-specific fluorescently labeled antibodies with fast (30 sec) binding. We implemented CoolMPS on MGIs PCR-free DNBSEQ MPS platform using arrays of 200nm DNA nanoballs (DNBs) generated by rolling circle replication and demonstrate 3-fold improvement in signal intensity and elimination of scar interference. Single-end 100-400 base and pair-end 2x150 base reads with high quality were readily generated with low out-of-phase incorporation. Furthermore, DNBs with less than 50 template copies were successfully sequenced by strong-signal CoolMPS with 3-times higher accuracy than in standard MPS. CoolMPS chemistry based on natural nucleobases has potential to provide longer, more accurate and less expensive MPS reads, including highly accurate "4-color sequencing" on the most efficient dye-crosstalk-free 2-color imagers with an estimated sequencing error rate of 0.00058% (one error in 170,000 base calls) in a proof-of-concept demonstration.

genomics↗

bioRxiv2020

The origin of domestication genes in goats

Goat domestication was critical for agriculture and civilization, but its underlying genetic changes and selection regimes remain unclear. Here we analyze the genomes of worldwide domestic goats, wild caprid species and historical remains, providing evidence of an ancient introgression event from a West Caucasian tur-like species to the ancestor of domestic goats. One introgressed locus with a strong signature of selection harbors the MUC6 gene which encodes a gastrointestinally secreted mucin. Experiments revealed that the nearly fixed introgressed haplotype confers enhanced immune resistance to gastrointestinal pathogens. Another locus with a strong signal of selection may be related to behavior. The selected alleles at these two loci emerged in domestic goats at least 7,200 and 8,100 years ago, respectively, and increased to high frequencies concurrent with the expansion of the ubiquitous modern mitochondrial haplogroup A. Tracking these archaeologically cryptic evolutionary transformations provides new insights into the mechanism of animal domestication. One Sentence SummaryGoat domestication mainly focused on immune and neural genes, with adaptive leaps driven by introgression and selection.

genomics↗

bioRxiv2019

Advanced Whole Genome Sequencing Using a Complete PCR-free Massively Parallel Sequencing (MPS) Workflow

BackgroundSystematic errors can be introduced from DNA amplification during massively parallel sequencing (MPS) library preparation and sequencing array formation. Polymerase chain reaction (PCR)-free genomic library preparation methods were previously shown to improve whole genome sequencing (WGS) quality on the Illumina platform, especially in calling insertions and deletions (InDels). We hypothesized that substantial InDel errors continue to be introduced by the remaining PCR step of DNA cluster generation. In addition to library preparation and sequencing, data analysis methods are also important for the accuracy of the output data.In recent years, several machine learning variant calling pipelines have emerged, which can correct the systematic errors from MPS and improve the data performance of variant calling. ResultsHere, PCR-free libraries were sequenced on the PCR-free DNBSEQ arrays from MGI Tech Co., Ltd. (referred to as MGI) to accomplish the first true PCR-free WGS which the whole process is truly not only PCR-free during library preparation but also PCR-free during sequencing. We demonstrated that PCR-based WGS libraries have significantly (about 5 times) more InDel errors than PCR-free libraries.Furthermore, PCR-free WGS libraries sequenced on the PCR-free DNBSEQ platform have up to 55% less InDel errors compared to the NovaSeq platform, confirming that DNA clusters contain PCR-generated errors.In addition, low coverage bias and less than 1% read duplication rate was reproducibly obtained in DNBSEQ PCR-free using either ultrasonic or enzymatic DNA fragmentation MGI kits combined with MGISEQ-2000. Meanwhile, variant calling performance (single-nucleotide polymorphisms (SNPs) F-score>99.94%, InDels F-score>99.6%) exceeded widely accepted standards using machine learning (ML) methods (DeepVariant or DNAscope). ConclusionsEnabled by the new PCR-free library preparation kits, ultra high-thoughput PCR-free sequencers and ML-based variant calling, true PCR-free DNBSEQ WGS provides a powerful solution for improving WGS accuracy while reducing cost and analysis time, thus facilitating future precision medicine, cohort studies, and large population genome projects.

genomics↗

bioRxiv2019

Unpaired Data Empowers Association Tests

To achieve a holistic view of the underlying mechanisms of human diseases, the biomedical research community is moving toward harvesting retrospective data available in Electronic Healthcare Records (EHRs). The first step for causal understanding is to perform association tests between types of potentially high-dimensional biomedical data, such as genetic, blood biomarkers, and imaging data. To obtain a reasonable power, current methods require a substantial sample size of individuals with both data modalities. This prevents researchers from using much larger EHR samples that include individuals with at least one data type, limits the power of the association test, and may result in higher false discovery rate. We present a new method called the Semi-paired Association Test (SAT) that makes use of both paired and unpaired data. In contrast to classical approaches, incorporating unpaired data allows SAT to produce better control of false discovery and, under some conditions, improve the association test power. We study the properties of SAT theoretically and empirically, through simulations and application to real studies in the context of Chronic Obstructive Pulmonary Disease. Our method identifies an association between the high-dimensional characterization of Computed Tomography (CT) chest images and blood biomarkers as well as the expression of dozens of genes involved in the immune system.

bioinformatics↗

bioRxiv2019

Biased neural coding of feature-based attention in human brain

Selective attention is a core cognitive function for efficient processing of information. Although it is well known that attention can modulate neural responses in many brain areas, the computational principles underlying attentional modulation remain unclear. Contrary to the prevailing view of a high-dimensional, distributed neural representation, here we show a surprisingly simple, biased neural representation for feature-based attention in a large dataset including five human fMRI studies. We found that when participants selected one feature from a compound stimulus, voxels in many cortical areas responded consistently higher to one attended feature over the other. This univariate bias was robust at the level of single brain areas and consistent across brain areas within individual subjects. Importantly, this univariate bias showed a progressively stronger magnitude along the cortical hierarchy. In frontoparietal areas, the bias was strongest and contributed largely to pattern-based decoding, whereas early visual areas lacked such a bias. These findings suggest a gradual transition from a more analog to a more abstract representation of attentional priority along the cortical hierarchy. Biased neural responses in high-level areas likely reflect a low-dimensional neural code that facilitates robust representation and simple read-out of cognitive variables.

neuroscience↗

bioRxiv2018

A missense mutation of Ip3r1 in Dp2 mice leads to short-term mydriasis and unfolded protein response in the iris constrictor muscles

Ip3r1 encodes an inositol 1,4,5-triphosphate-responsive calcium channel. Mutations in the Ip3r1 gene in humans may cause Gillespie syndrome (GS) typically presents as fixed dilated pupils in affected infants, which was referred to as iris hypoplasia. However, there is no report of mice with Ip3r1 heterozygous mutations showing dilated pupils. Here, we report a new Ip3r1 allele (dilated pupil 2; Dp2) with short-term dilated pupil phenotype derived from an N-ethyl-N-nitrosourea (ENU) mutagenesis screen. This allele carries a G5927A transition mutation, which is predicted to result in a C1976Y amino acid change in the open reading frame. Histology and pharmacological tests show that the dilated pupil phenotype is a mydriasis caused by the functional defect in the iris constrictor muscles in Dp2. The dilated pupil phenotype in Dp2 was referred to as mydriasis and excluding iris hypoplasia. IHC analysis revealed increased expression of BIP protein, the master regulator of unfolded protein response (UPR) signaling, in Dp2 mice that did not recover. Apart from the dilated pupil phenotype (mydriasis), there are no other abnormal phenotypes including Ip3r1-related ataxia that may be found. This study is the first report of an Ip3r1 mutation being associated with the mydriasis phenotype. Dp2 mice represent a valuable self-healing model that may be used to study the therapeutic approach for Ip3r1-related diseases or diseases caused by similar pathomechanisms.

genetics↗

bioRxiv2017

Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues

Skeletal muscle comprises a family of diverse tissues with highly specialized morphology, function, and metabolism. Many acquired diseases - including HIV, COPD, cancer cachexia, critical illness myopathy, and sepsis - affect specific muscles while sparing others. Even monogenic muscular dystrophies tend to selectively affect certain muscle groups, despite their causative genetic mutations being present in all tissues. These observations suggest that factors intrinsic to muscle tissues influence their susceptibility to various disease mechanisms. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNA sequencing (RNA-seq) to profile global mRNA expression in a wide array of skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. This diversity is only partly explained by fiber type composition and developmental history, suggesting that specialized transcriptional profiles establish the functional identity of muscle tissues. We find conservation in the transcriptional profiles across species as well as between males and females, indicating that these data may be useful in predicting gene expression in related species. Notably, thousands of differentially expressed genes in skeletal muscle are associated with human disease, and hundreds of these genes encode targets of drugs on the market today. We detect mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. In addition to demonstrating the intrinsic diversity of skeletal muscles, these data provide a resource for generating testable hypotheses regarding the mechanisms that establish differential disease susceptibility in muscle.\n\nSignificance StatementSkeletal muscles are a diverse family of tissues with a common contractile function but divergent morphology, development, and metabolism. One need only reflect on the different functions of limb muscles and the diaphragm to realize the highly specialized nature of these tissues. Nevertheless, every study of global gene expression has analyzed at most one representative skeletal muscle. Here we measure gene expression from 11 different skeletal muscles in mice and rats. We show that there is no such thing as a representative skeletal muscle, as gene expression profiles vary widely among the tissues analyzed. These data are an important resource for pharmacologists, tissue engineers, and investigators studying the mechanisms of cellular specialization.

systems biology↗